OXIDATIVE STABILITY AND SENSORY QUALITY OF FOODS FRIED IN PALM AND OTHER VEGETABLE OIL BLENDS

By

CAITLYN J. SORIANO

A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF

FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2016

© 2016 Caitlyn J. Soriano

To my Mom and Dad

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ACKNOWLEDGEMENTS

First I would like to thank my advisor, Dr. George Baker, for granting me the

opportunity to pursue my master’s degree under his tutelage and to the Malaysian Palm

Oil Board for funding my graduate program. I would also like to extend my sincere

appreciation to the rest of my supervisory committee: Dr. Deborah Burr, Dr. Renee

Goodrich-Schneider, Dr. Paul Sarnoski, and Dr. Charles Sims, for their guidance and

expertise throughout my studies. A special thank you goes to Sara Marshall, Dr. Asli

Odabasi, and the FSHN Taste Panel Staff for their assistance with sensory evaluations

and to Dr. Yavuz Yagiz for his assistance with instrumental analyses. I would also like to

thank my lab mates, near, far, and adjunct: Dan, Hai, Rui, Brittany, and Gayathri for all

of their help, suggestions, and friendship and my roommate, Izzy, for all of the late

nights, early mornings, and pots of coffee. Additionally, I would like to thank Dr. Baker,

Dr. Gloria Cagampang, Dr. Harry Sitren, and the 2013 China group for introducing me

to the world of food science. And last but definitely not least, I would like to thank my

boyfriend, Amith, and my parents, Madolin and Edwin, for their never ending love,

patience, and support.

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TABLE OF CONTENTS page

ACKNOWLEDGEMENTS ............................................................................................... 4

LIST OF TABLES ............................................................................................................ 7

LIST OF FIGURES .......................................................................................................... 8

LIST OF ABBREVIATIONS ............................................................................................. 9

ABSTRACT ................................................................................................................... 11

CHAPTER

1 INTRODUCTION .................................................................................................... 13

2 LITERATURE REVIEW .......................................................................................... 15

Palm Oil .................................................................................................................. 15

Production ........................................................................................................ 17 Refining, Bleaching, and Deodorization ........................................................... 18 Fractionation ..................................................................................................... 20

Oil Modification ................................................................................................. 22 Economics ........................................................................................................ 26

Deep Fat Frying ...................................................................................................... 26 Frying Phases .................................................................................................. 27

Chemical Reactions ......................................................................................... 29 Oil Quality ............................................................................................................... 32

Oil Stability Index .............................................................................................. 35

Other Factors Affecting Oil Quality ................................................................... 38 Sensory Science ..................................................................................................... 38

Testing.............................................................................................................. 40 Scales............................................................................................................... 41 Evaluation ......................................................................................................... 43

3 MATERIALS AND METHODS ................................................................................ 50

Materials ................................................................................................................. 50 Sample Preparation ................................................................................................ 50

Fatty Acid Composition ........................................................................................... 51

Oxidative Stability Index .......................................................................................... 52 Melting Range ......................................................................................................... 52 Deep-Fat Frying ...................................................................................................... 53 Color ....................................................................................................................... 54 Free Fatty Acids ...................................................................................................... 54 Volatile Compound Analysis ................................................................................... 55 Sensory Evaluation ................................................................................................. 55

6

Statistics ................................................................................................................. 56

4 RESULTS AND DISCUSSION ............................................................................... 61

Blend Screening ..................................................................................................... 61

Fatty Acid Composition ........................................................................................... 62 Free Fatty Acid ....................................................................................................... 62 Volatile Compound Analysis ................................................................................... 63 Color ....................................................................................................................... 64 Sensory ................................................................................................................... 66

5 CONCLUSIONS ..................................................................................................... 76

APPENDIX

A BALLOT FOR SENSORY EVALUATION ............................................................... 78

B DESCRIPTIVE SUMMARY STATISTICS FOR MISSING DATA: 40/60 PC ........... 82

C DESCRIPTIVE SUMMARY STATISTICS FOR MISSING DATA: SOYBEAN ......... 83

LIST OF REFERENCES ............................................................................................... 84

BIOGRAPHICAL SKETCH ............................................................................................ 93

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LIST OF TABLES

Table page 2-1 Fatty acid composition of various vegetable oils................................................. 45

2-2 Desirable qualities of refined palm oil ................................................................. 45

2-3 Oxidative stability index (OSI) values at 120°C .................................................. 45

2-4 AOCS Flavor Quality Scale ................................................................................ 46

3-1 Palm and other vegetable oil blend combinations (%) ........................................ 58

3-2 Palm kernel and other vegetable oil blend combinations (%) ............................. 58

3-3 Time equivalent per batch .................................................................................. 59

4-1 Values for pure vegetable oils ............................................................................ 69

4-2 Values for palm and other vegetable oil blend combinations .............................. 69

4-3 Values for palm kernel and other vegetable oil blend combinations ................... 69

4-4 Fatty acid composition of 40/60 PC over time (%) (n=3) .................................... 70

4-5 Fatty acid composition of soybean oil over time (%) (n=3) ................................. 70

4-6 Free fatty acid (FFA) values for oils over time (n=3) ........................................... 70

4-7 Color values of frying oils with increasing frying time (n=2) ................................ 70

4-8 Hedonic means for overall appearance (n=93) ................................................... 70

4-9 Hedonic means for overall liking (n=93) ............................................................. 71

4-10 Hedonic means for overall flavor (n=93) ............................................................. 71

4-11 Hedonic means for off-flavor (n=93) ................................................................... 71

4-12 Hedonic means for overall texture (n=93) ........................................................... 71

4-13 Hedonic means for crispiness (n=93) ................................................................. 71

4-14 Juiciness means using JAR scale (n=93) ........................................................... 72

4-15 Purchase intent means using 5-point scale (n=93) ............................................. 72

4-16 Panelist preference of prepared chicken wing sections ...................................... 72

8

LIST OF FIGURES

Figure page 2-1 Flow diagram of a palm oil mill ........................................................................... 47

2-2 Frying oil quality curve ........................................................................................ 47

2-3 Deep fat frying diagram ...................................................................................... 48

2-4 Physical and chemical changes of oil during deep-fat frying .............................. 48

2-5 Example of OSI output from Professional Rancimat™ 892 ................................ 49

2-6 Example of an unmarked hedonic line scale ...................................................... 49

3-1 Flow chart for frying chicken wing sections and sampling of wings and oils ....... 60

4-1 Chromatogram of identified volatiles for chicken wing sections fried in 40/60 PC Hour 0* (Batch 1) .......................................................................................... 73

4-2 Chromatogram of identified volatiles for chicken wing sections fried in 40/60 PC Hour 26.5 (Batch 14) .................................................................................... 73

4-3 Chromatogram of identified volatiles for chicken wing sections fried in 40/60 PC Hour 53 (Batch 26) ....................................................................................... 74

4-4 Chromatogram of identified volatiles for chicken wing sections fried in soybean oil Hour 0*(Batch 1) .............................................................................. 74

4-5 Chromatogram of identified volatiles for chicken wing sections fried in soybean oil Hour 26.5 (Batch 14) ....................................................................... 75

4-6 Chromatogram of identified volatiles for chicken wing sections fried in soybean oil Hour 53 (Batch 26) .......................................................................... 75

9

LIST OF ABBREVIATIONS

40/60 PC 40% palm/ 60% canola oil blend

ANOVA analysis of variance

AOM active oxygen method

AV acid value

C canola oil

CIE International Commission on Illumination

CV carbonyl value

FAMEs fatty acid methyl esters

FAO Food and Agricultural Organization

FDA Food and Drug Administration

FFA free fatty acids

FID flame ionization detector

GC/MS gas chromatography/mass spectrometry

GLA γ-linolenic acid

GRAS generally recognized as safe

HSD honestly significant difference

JAR just-about-right

LDL low density lipoprotein

NDB neutralized, bleached, deodorized

OSI oil stability index

PFAD palm fatty acid palmitate

PHOs partially hydrogenated oils

PK palm kernel oil

P palm oil

10

ppm parts per million

PV peroxide value

QDA quantitative descriptive analysis

RBD refined, bleached, deodorized

S soybean oil

SPME solid phase microextraction

STP standard temperature and pressure

TAG Triacylglycerol

USD United States dollar

USDA United States Department of Agriculture

VAS visual analog system

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Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science

OXIDATIVE STABILITY AND SENSORY QUALITY OF FOODS FRIED IN PALM AND

OTHER VEGETABLE OIL BLENDS

By

Caitlyn J. Soriano

August 2016

Chair: George Baker Major: Food Science and Human Nutrition

Vegetable oils containing unsaturated fatty acids are more susceptible to

oxidation than those containing saturated fatty acids. To increase oxidative stability,

vegetable oils may be chemically modified through hydrogenation. Partially

hydrogenated oils (PHOs) have been used for optimal shelf life and textural

considerations of food products (Stevenson and others 1984). However, during

hydrogenation, double bonds can rearrange into the trans- isomer geometric

configuration. The National Academy of Science’s Institute of Medicine identified a

direct correlation between consumption of trans- fat, increased levels of LDL

cholesterol, and risk for cardiovascular diseases. With the recent FDA decision to

eliminate PHOs by 2018, there is a need for alternative frying oils derived from natural

fats.

The objective of this study was to compare oxidative stability and sensory quality

of foods fried in palm and other vegetable oil blends to current frying oils. Fresh,

unbreaded chicken wing sections were fried in a 40% palm/ 60% canola oil blend and

pure soybean oil at 175±5°C. Both oils were used to fry wings for 53 hours over three

days. Oils sampled from Hour 0, Hour 26.5, and Hour 53 were analyzed by analytical

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instrumentation. Chicken wings were evaluated by sensory analysis for consumer

acceptance each day by 106, 96, and 93 panelists, respectively.

Chemical analyses of oil quality demonstrated evidence of lipid oxidation by

decreases of polyunsaturated fatty acids (PUFAs) in fatty acid composition, formation of

volatile secondary oxidation compounds, minimal hydrolytic deterioration, and darkening

and reddening of oil color. Untrained sensory panels indicated no significant differences

between chicken wings fried in 40% palm/ 60% canola oil blend and soybean oil for

overall appearance, off-flavor, overall texture, crispiness, juiciness, and purchase intent.

Significant differences (P <0.05) were seen in overall flavor and overall liking after two

and three days of frying. Chicken wings fried in 40% palm/ 60% canola oil blend were

more preferred or similarly preferred to soybean oil. Chemical and sensory analyses

conclude 40% palm/ 60% canola oil blend to be an acceptable alternative frying oil

compared to soybean oil.

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CHAPTER 1 INTRODUCTION

Deep-fat frying is an industrial cooking method resulting in desirable flavor and

texture attributed to fried foods. Foods immersed in hot oil (150-190°C) and fried under

ideal conditions yield golden brown color, fully cooked interior, crispy surface, and

optimal oil absorption. Frying oil is subjected to elevated temperatures with oxygen and

moisture catalyzing hydrolysis, oxidation, and polymerization chemical reactions. Deep

fat frying results in physical and chemical changes of frying oil, decreases in

unsaturation, and increases in foaming, color, viscosity, density, specific heat, free fatty

acids, and total polar materials. Frying oil should be discarded if no longer

organoleptically acceptable, if the total polar materials are greater than 25%, if the acid

value is greater than 2.5, or if the smoke point is lower than 170°C (Paul and Mittal

1997). However, in some restaurants or factories, an experienced cook subjectively

determines discard time by observing color, odor, smoke, or foaming because the

aforementioned tests are chemically and financially unsuitable (Morton and Chidley

1988).

Animal fats and vegetable oils are used to deep-fat fry foods. Vegetable oils

contain more polyunsaturated fatty acids and thus are more susceptible to oxidation. To

increase oxidative stability, vegetable oils are modified by chemical hydrogenation.

However, partially hydrogenated oils contain trans- fatty acids which are associated with

increased LDL cholesterol and risk of cardiovascular disease. Blending oils with

different physical properties may create a frying matrix more resistant to oxidation and

performance characteristics similar to partially hydrogenated oils. Optimal oil blends

may be developed with enhanced oxidative stability, flavor formation, pourability at room

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temperature, and competitive cost of production when compared to traditional vegetable

oil sources.

Chicken wings are a Western-style food that has become globally popular for

their convenience in preparation and consumption (Barbut 2012). The objectives of this

research were a) to develop palm or palm kernel oil combined with other vegetable oil

blends and to screen for blends with the longest predicted fry-life and pourability at

room temperature, and b) to determine if chicken wings fried in the selected blend

would produce an acceptable alternative to chicken wings fried in soybean oil by

comparing chemical, instrumental, and sensory analytical parameters between resulting

fried chicken products. To date, no studies have been published analyzing the deep-fat

fry life of palm oil blends used to prepare fired chicken wings for organoleptic

acceptability. This study intends to benefit the fried food industry by providing an

alternative frying oil that produces a long fry life, is sensorially acceptable, and is

healthier compared to hydrogenated oil sources.

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CHAPTER 2 LITERATURE REVIEW

Palm Oil

Palm oil is the most consumed vegetable oil worldwide (Statista 2016a). During

2014-2015, palm oil accounted for 62.4% of the global production of edible vegetable oil

(Statista 2016b) with Indonesia leading production at 52.7% (USDA 2016).Oil palm is a

tree whose fruits are used for extraction of edible oil. Originating in Africa, the oil palm

has since then been cultivated in other tropical areas of the world such as Central and

northern South America, as well as Asian countries near the Equator. Elaeis, meaning

oil in Greek, is a palm genus with two natural species: Elaeis guineensis, the African oil

palm, and Elaeis oleifera, the American oil palm. However, genetic breeding has

developed three hybrid varieties: dura, pisifera, and tenera. Tenera is a cross-breed of

the dura and pisifera and accounts for a 30% increase in oil yield without altering total

dry matter (Corley and Lee 1992). Oil palm fruit begins to develop 3 years after planting

and can be harvested for up to 25 years. The reddish-yellow fruit is harvested from

fresh fruit bunches, weighing 10-40 kg and containing approximately 2,000 fruit. Each

fruit is composed of three components: yellow fleshy pulp called the mesocarp, a seed

coating, and a palm kernel. By definition, palm oil is derived from the mesocarp, and

palm kernel oil is derived from the seed (FAO 2002). Tenera will yield 4.0 tons of palm

oil per hectare and 0.5 tons of palm kernel oil per hectare (Sue 2009).

Palm oil has a fatty acid composition of palmitic acid (16:0) [43.7%], oleic acid

(18:1) [40.0%], linoleic acid (18:2) [10.5%], stearic acid (18:0) [4.75%], myristic acid

(14:0) [1.25%] and trace amounts of lauric acid (12:0) and linolenic acid (18:3) (Table 2-

1) (FAO 2001). Comprised of more than 45% saturated fatty acids, palm oil is solid at

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room temperature with a melting range of 33.8-39.2°C (Sue 2009). Palm kernel oil has a

fatty acid composition of lauric acid (12:0) [50.0%], myristic acid (14:0) [16.0%], oleic

acid (18:1ω9) [15.5%], palmitic acid (16:0) [8.25%], linoleic acid (18:2) [2.25%], stearic

acid (18:0) [2.0%] and trace amounts of linolenic acid (18:3 ω3) (Table 2-1) (FAO 2001).

Palm kernel oil is semi-solid at room temperature with a melting range of 25.9-28.7°C

(Sue 2009). The sharp melting range and crystallization behavior of palm kernel oil

indicate its effective use in confectionary applications (Sue 2009). Due to the fatty acid

composition of palm and palm kernel oil, both oils can be subjected to fractionation,

separation into liquid and soild fractions, to provide different uses in the food industry.

In addition to triglycerides and small amounts of mono- and diglycerides, crude

(unrefined) palm oil contains other minor components, too. These include carotenoids,

tocopherols, sterols, phosphatides, triterpenic and aliphatic alcohols (Basiron 2005).

While these minor components comprise less than 1% of palm oil, they affect palm oil

stability and refinability. Crude palm oil contains 500-700 ppm carotenoids and 600-

1000 ppm tocopherols and tocotrienols. Unless extracted before processing,

carotenoids in the form of alpha- and beta- carotenes are thermally destroyed during

deodorization to yield desirable neutral color for refined, bleached, and deodorized

(RBD) oil. However, in crude palm oil, carotenoids exhibit a protective effect against

oxidation by oxidizing prior to triglycerides (Basiron 2005).Tocopherols and tocotrienols

in the alpha- and gamma- form are natural antioxidants. The collected effects of

carotenoids, tocopherols, tocotrienols, and high unsaturated content contribute to palm

oil’s oxidative stability.

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Production

The production of crude palm oil and palm kernel oil occur in stages: fruit

reception, sterilization, stripping, digestion, oil extraction, clarification, storage, nut and

fiber separation, and nut and kernel treatment (Figure 2-1) (Basiron 2005). Good quality

palm oil results from proper handling of fruit. Fresh fruit bunches are transported from

lorries, or trailers, to sterilizer cages. Fruit are subjected to steam pressure of 3 kg/cm2

at 143°C for 60 min. Sterilization prevents further increases in free fatty acid due to

enzymatic reaction, facilitates mechanical stripping, prepares pericarp for further

processing, and preconditions kernels to minimize breakage. Sterilized fruit is then

separated from bunch stalks through vigorous shaking and beating via a drum stripper.

Once separated, the fruit undergo digestion to reheat sterilized fruits, loosening pericarp

from nut and opening up oil cells before extraction. Oil is extracted using a continuous

screw press resulting in a mixture of oil, water, and solids, and a press cake of fiber and

nuts. At this stage, crude palm oil is composed of 66% oil, 24% water, and 10% nonoily

solids. Once diluted with water, crude palm oil is screened to remove fibrous material

and then separated into oil and sludge. The top oil layer is purified, dried, cooled, and

then pumped into storage tanks. The sludge layer is approximately 10% oil and is

returned to the combined oil/sludge settling tank to be separated again. The press cake

passes along a breaking conveyor to a column with an upward airflow of 6 m/s. This

allows fibers to be held in suspension and nuts to drop to the bottom. Fibers are sent to

be used as boiler fuel, and the nuts are sent to be conditioned.

Kernel treatment involves four functions: conditioning, cracking, kernel and shell

separation, and kernel drying (Basiron 2005). Warm kernels from press cake are dried

sufficiently to loosen kernels and cooled to harden shells before cracking. Proper

18

conditioning allows shells to crack cleanly into two or more pieces releasing a whole

kernel. Typically cracking occurs as nuts are launched against a stator ring. More recent

technology developed a ripple mill in which nuts are forced between a stationary ripple

plate and rotor. This new technology eliminates the need for nut conditioning. Nuts and

shells are then separated by a winnowing system, eliminating small debris, and placed

into a claybath with specific gravity of 1.12. At this specific gravity, kernels will float and

shell will sink. Fresh kernels have a moisture content of 20% and would result in mold

growth if bagged. Kernels are then dried to 7% moisture before bagging and storage.

Refining, Bleaching, and Deodorization

Physical refining and chemical refining are both used to produce refined,

bleached, and deodorized (RBD) palm oil suitable for edible purposes. Physical refining

is more often used due to cost effectiveness, efficiency, and simple effluent treatments.

Physical refining was introduced in 1973 and consists of two major stages: pretreatment

and deodorization. Pretreatment is the initial degumming of crude palm oil with

concentrated phosphoric acid (80-85% concentration) and adsorptive cleansing with

bleaching clay. Phosphoric acid precipitates non-hydratable phosphatides and

bleaching earth adsorbs undesirable impurities, reduces oxidation products, adsorbs

phospholipids precipitated by phosphoric acid, and removes any excess phosphoric

acid. Residual phosphoric acid can result in increased free fatty acids (FFA) levels and

off color in RBD oil. To ensure oil quality, calcium carbonate is added after bleaching

earth to neutralize residual acid. The slurry is filtered to recover oil and diatomaceous

earth is added to improve filtration. Recovered oil undergoes a second filtration to

remove excess diatomaceous earth. Filtered earth contains 20-40% oil and comprises

the most oil waste during refining. After pretreatment, pretreated oil is subjected to

19

deacidification and deodorization. The oil is deaerated and then heated to 240-270°C to

remove free fatty acids and volatile aldehydes and ketones that contribute to off-flavor

and odor. Residual carotenoids are also thermally decomposed resulting in light-

colored, bland RBD palm oil (Willems and Padley 1985).

Chemical refining or caustic refining is consists of three stages: gum conditioning

and neutralization, bleaching and filtration, and deodorization. During gum conditioning,

crude oil is heated to 80-90°C and phosphoric acid (80-85%) is dosed to precipitate

phospholipids. Then caustic soda is dosed to react with FFA forming sodium soap that

is easily centrifuged for removal. The oil is then washed and dried to moisture level <

0.05%. Neutralized palm oil is treated with bleaching earth similar to physical refining

but bleaching earth is removed to eliminate traces of soap. Deodorization step is similar

to physical refining, however, direct steam injection is used to remove residual fatty

acids, volatile oxidation products, and odiferous materials, resulting in neutralized,

bleached, deodorized (NBD) palm oil. Comparable to chemical refining, physical refining

allows deacidification, deodorization, and thermal decomposition occur in one process.

Desirable qualities of RBD palm oil is shown in Table 2-2 (Basiron 2005).

Byproducts of physical refining are palm fatty acid distillate (PFAD). PFAD is the

condensate of volatile components removed from deodorizer by stripping steam. It

contains vitamin E as tocopherols and tocotrienols and is approximately 80-90% FFA. It

is used as raw materials for soap making, feed compounding, and oleochemical

feedstock. Chemical refining results in soapstock as a byproduct. Soapstock is treated

with dilute sulfuric acid to form palm acid oil. Palm acid oil consists of >50% FFA,

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neutral oil, and 2-3% moisture and other impurities. It is used for formulation of laundry

soaps and calcium soaps for animal feed (Basiron 2005).

Fractionation

Two methods of fractionation for palm oil are used in industry: dry fractionation

and fractionation using detergent (Deffense 1985). Dry fractionation is categorized into

fast dry and slow dry. The Bernardini and Extraction de Smet methods are common fast

dry techniques. Bernardini utilizes a batch crystallizer agitating cooled oil from 35°C to

16°C. The radial filter separates fractions by vacuum suction of palm olein leaving palm

stearin on the surface. The de Smet technique is similar with rapid cooling of oil to 19°C

in a crystallizer with a large surface area and use of a Stockdale filter to separate

fractions. Conversely the Tirtiaux method, a slow dry technique, subjects oil to slow

cooling to control the latent heat of crystallization ad minimize supercooling. Detergent

fractionation involves chilling palm oil in the presence of magnesium sulfate to 20°C and

another detergent, such as sodium lauryl sulfate with magnesium or sodium sulfate, is

added. Once cooled the partially crystallized oil is mixed with a detergent, and the

crystals pass into the aqueous phase. A centrifuge can then be used to separate the

olein from the stearin/detergent mix, and the stearin/detergent mix can be centrifuged

again to obtain stearin. With either method the resulting fractions are liquid phase olein

and solid phase stearin.

Palm oil subjected to fractionation results in palm olein and palm stearin. Palm

olein is separated into two grades: standard palm olein and super olein. Standard palm

olein has a fatty acid composition of oleic acid (18:1) [42.9%], palmitic acid (16:0)

[40.8%], linoleic acid (18:2) [11.8%], stearic acid (18:0) [4.3%] (FAO 2001) and melting

range of 19.2-23.6°C (Sue 2009) Super olein has a fatty acid profile of oleic acid (18:1)

21

[45.1%], palmitic acid (16:0) [35.4%], and linoleic acid (18:2) [13.4%] (FAO 2001) and

melting range of 12.9-16.6°C (Sue 2009). Palm olein and super olein can be

differentiated by iodine value. Iodine value (IV) measures the degree of unsaturation,

and super olein is palm olein with IV > 60. Palm olein and super olein are commonly

used in industrial frying because of several advantages. The fatty acid profile of olein is

ideal for frying as linolenic acid is present only in trace amounts. Oxidation of linolenic

acid during deep-fat frying contributes to fishy odor and decreases fruity and nutty odor

(Choe and Min 2007). Olein is highly resistant to oxidation, has a longer shelf-life, and is

naturally trans-fat free unlike other suitable frying oils (Basiron 2005). Olein also has a

lower melting range than palm oil, resulting in better mouth feel, product gloss, and

immediate circulation of oil upon heating (Matthaus 2007). Palm stearin has a fatty acid

composition of palmitic acid (16:0) [59%], oleic acid (18:1) [27.4%], linoleic acid (18:2)

[7.0%], stearic acid (18:0) [4.8%], and myristic acid (14:0) [1.4%] (FAO 2001), and a

melting range of 46.6-53.8°C (Sue 2009). Palm stearin is used as starting materials for

palm mid fractions as well as forming blends with other vegetable oils to make

functional products such as margarines and shortenings.

Palm kernel oil subjected to fractionation results in palm kernel olein and palm

kernel stearin. Palm kernel olein has as a fatty acid composition of lauric acid (12:0)

[44.7%], oleic acid (18:1) [19.2%], myristic acid (14:0) [14.0%], palmitic acid (16:0)

[8.3%], linoleic acid (18:2) [3.3%], and stearic acid (18:0) [2.3%] (FAO 2001), and a

melting point of 25°C (Sue 2009). Palm kernel stearin has a fatty acid composition of

lauric acid (12:0) [56.6%], myristic acid (14:0) [22.4%], palmitic acid (16:0) [8.0%], oleic

acid (18:1) [5.6%], and stearic acid (18:0) [1.8%] (FAO 2001), with a melting point of

22

35°C (Sue 2009). The sharp melting point of solid fat in palm kernel stearin makes it

desirable for confectionary products.

Oil Modification

To stabilize frying oil, the most common solution is to modify the fatty acid

composition of the oil (Romano and others 2012). There are several methods including

hydrogenation, interesterification, genetic modification, and blending.

Most vegetable oils contain high levels of polyunsaturated fatty acids which

increases their vulnerability to oxidation. To retard oxidation rate, polyunsaturated

vegetable oils are hydrogenated. In 1901, Wilhelm Normann showed liquid oils could be

hydrogenated and patented the process in 1902 (Musson 1965). Hydrogenation is used

to alter oil properties for very specific application and functions. Applications of

hydrogenation are to provide taste and smell stability, enhance shelf-life of products

containing unsaturated fatty acids, and alteration of functional characteristics in naturally

occurring fats (McClements and others 2008).

Hydrogen gas is bubbled through heated oil in the presence of catalysts (nickel,

platinum, etc.) at controlled temperature and pressure inside a reaction vessel. During

hydrogenation, carbon-carbon double bonds of fatty acids are saturated with hydrogen,

resulting in the conversion of liquid oil and soft fats to hard or plastic fats. Complete

hydrogenation of unsaturated fatty acids eliminates all double bonds and yields a

completely saturated fat with extremely dense crystalline properties unlike anything

encountered in natural fats. However, with insufficient hydrogen available for complete

saturation, the double bond reforms as trans- isomers, forming partially hydrogenated

oils (McClements and others 2008). Thus, hydrogenation affects fat properties and

geometric isomerization. Under normal conditions, the melting point of all-cis-linolenic

23

acid is -13°C, stearic acid is 70°C, cis-oleic acid 16°C, while trans-oleic acid is 44°C

(Farr 1987).

In some applications, such as baking or frying, that traditionally employ butter or

ghee, partial hydrogenation of vegetable oils was developed as a functional alternative

(Ascherio and Willett 1997). The purpose of partial hydrogenation is selective saturation

of polyunsaturated fats to monounsaturated or saturated fatty acids for improved

stability. However, this process results in production of trans- fatty acids. In 2002, the

National Academy of Science’s Institute of Medicine identified a direct correlation

between consumption of trans- fat and increased levels of LDL cholesterol and

increased risk for cardiovascular disease (FDA 2015). Other human health concerns

have also been connected to trans- fat consumption such as, worsening insulin

resistance, increased diabetes risk, and higher risk of impaired growth for fetuses

because of the mother’s consumption of trans- fatty acids, although further confirmation

is still required (Federal Register 2015). In June 2015, the FDA issued the removal of

PHOs from the general recognized as safe (GRAS) list by 2018. Therefore, there is a

need for alternative frying oils derived from natural fats.

Interesterification is a chemical modification process involving rearrangement of

fatty acids of two of more trigacylglycerol (TAG) molecules resulting in a different fatty

acid profile on a triglyceride (Rousseau and Marangoni 2002). Interesterification

typically involves random rearrangement, but directed interesterification also occurs

using low controlled temperature to remove crystallized saturated fats from reaction

vessel.

24

Genetic modification alters the fatty acid composition of plants by altering

enzyme pathways in the plant’s metabolic function producing unsaturated fatty acids.

Most genetically modified vegetable oils are developed for commercial use and contain

elevated oleic acid levels for purposes of oxidative stability by double bond removal

(McClements and others 2008).

Blending natural fats with high levels of polyunsaturated fatty acids together with

other fats containing more saturated fatty acids result in a suitable blend for frying with

improved stability. Liquid or base oil, such as traditional canola or soybean oil or palm

olein, is blended with a natural hard stock, naturally solid fat (Michels and Sacks 1995),

such as palm stearin or palm kernel stearin to create an optimal frying blend. Blended

oils as a food ingredient tend to function poorly in shelf-stable foods as the component

with lower melting range would begin to leach out during storage affecting appearance,

texture, and mouthfeel. For example, a shelf-stable baked good made with blended oils

would develop oil stains on its packaging from oil leaching. However, at elevated

temperatures used in frying, blends are heated, allowing additional space between

TAGs compared to normal STP crystalline behaviors as liquid oils, dispersed, and

continuously intermixed in the fryer. Oil blends tend to be resistant to oxidation, suited to

high or low turnover rates, and provide good shelf-life stability (Stevenson and others

1984).

The fatty acid composition of a vegetable oil serves to define its stability.

Linolenic acid (18:3) is highly susceptible to oxidation, as it contains three double bonds

allowing oxygen attack and hydrogen abstraction at adjacent carbons to double bond

systems of unsaturated fatty acids. As the degree of unsaturation of the oil increases, its

25

resistance to oxidation decreases. According to Frankel and others (1992), as the

number of double bonds increase in fatty acids containing 18 carbons in their linear

chain, their oxidation rate increases as a ratio of 1:10:100:200 corresponding to 0, 1, 2,

and 3 double bonds, respectively. Linolenic acid oxidation products also contribute to

“painty” smelling and tasting off-flavors found in oil. Therefore, linolenic acid (18:3)

content of food ingredients should be limited to less than 3% of the total fatty acid

composition. Furthermore, linoleic acid (18:2) is also susceptible to oxidation, but should

account for a greater percentage than linolenic acid to provide an ideal deep fried flavor

and potentially mask off-flavors from lipid oxidation. High oleic oils have better frying

stability but low desirable deep-fried flavor because of the fairly stable oleic acid

(Warner and Gupta 2005).

Fat conventionally refers to a lipid that is solid at room temperature, while oil

refers to a lipid that is liquid at room temperature (Walstra 2003). Melting behavior of

fats and oils depend on packing of TAG molecules within the crystal formed, where

more effective packing results in higher melting ranges (Walstra 2003). Melting ranges

of pure TAGs increase with chain length, are higher for saturated than unsaturated, and

are higher for straight-chained than branched TAGs. Lipid crystallization determines its

influence on physicochemical and sensory properties in foods (McClements and others

2008).

Commercially used frying oils are the pourable type with suspended solids or

plastic type (Aini and Miskandar 2007). However, plastic type frying fats lack the

lubricity component of ease of handling (how pourable the product is) (Bessler and

Orthoefer 1983).The optimal frying oil blend is highly resistant to oxidation, has a low

26

acid value, a low initial level of free fatty acids, pourable at room temperature (Bessler

and Orthoefer 1983), and a low rate of smoking, foaming, and darkening (Sue 2009).

Economics

Worldwide, the production of palm oil totals to 65.39 million metric tons, and the

production of palm kernel oil totals to 7.66 million metric tons (USDA 2016). Employing

the use of palm oil in food applications requiring solid fats offer technical and economic

advantages. Cost savings in many situations are attributed to lower costs of raw

materials, reduction of cost from minimal process losses, and longer oxidative stability

of palm oil in frying applications. It is estimated 2 kg of phosphoric acid, 2.5 kg of caustic

soda, and 30 kg of bleaching earth are required to refine 1 metric ton of crude palm oil

(Basiron 2005). Liquid oils require catalysts, such as nickel, to undergo hydrogenation,

whereas hydrogenation of palm oil is not necessary to achieve oxidative stability.

According to the United States Department of Agriculture (USDA) in 2016, the

average price of soybean oil is $635 per metric ton, compared to $789 for canola and

$577 for palm oil per metric ton. Basiron (2005) estimated fractionation cost of palm oil

as $5.55 per metric ton.

Deep Fat Frying

Deep fat frying is a common, practical industrial method of cooking requiring

minimal preparation that yields desirable fried food flavor and texture of foods. In 2005

the United States fried food industry was estimated to be worth $83 billion and double

that ($166 billion USD) for rest of the world (Pedreschi and others 2005). Food products

immersed in hot oil interact with surface air at temperatures (150-190°C), along with the

components of the food being fried, resulting in desirable flavor and texture of fried

foods (Blumenthal 1991). Al-Kahtani (1991), who analyzed frying conditions in sixty-two

27

restaurants, showed how often restaurants change their frying oil, ranging from 3 h for 2

days using palm oil to 16 h for 8 days using hydrogenated vegetable oil. Foods fried at

ideal conditions produce golden brown color, fully cooked centers, crispy surfaces, and

optimal oil absorption. Foods fried with shorter fry times or lower temperatures, are

categorized as “underfried,” and are characterized by lighter colors, partially cooked

centers, and absence of desirable texture. Foods fried with longer fry times or higher

temperatures, are categorized as “overfried,” and are characterized by darker colors,

harder exteriors, and greasy textures from excess oil absorption (Blumenthal 1991).

Fresh oil that approaches 175°C will not produce color or flavor characteristic of oil that

has been thermally “conditioned” prior to frying. Blumenthal (1991) describes frying

quality of oil in five phases, break-in; fresh; optimum; degrading; and runaway, with

each phase progressing in respective order as frying time increases (Figure 2-2).

Examples of quality parameters using deep fried potato strips are provided:

Break-in oil produces raw, ungelatinized starch centers, no cooked odors, and a non-crispy/soggy surface

Fresh oil produces slight browning on their edges, partial gelatinization of starch, and some surface absorption

Optimum oil produces golden-brown color, crisp surface, desirable odors, and fully cooked centers

Degrading oil produces darkened/spotty surfaces, excess oil absorption, and case-hardened limpness

Runaway oil produces dark, case-hardened surfaces, excess oil absorption, partially cooked centers, off-odors and flavors, and a collapsing interior

Frying Phases

There are three phases of deep-fat frying: moisture transfer, oil transfer, and

cooking of interior (Blumenthal 1991, Stevenson and others 1984). Moisture transfer

28

occurs once food is placed into hot oil. Moisture on the outer surface of the food product

converts to water vapor and releases into the oil. Moisture from the interior core moves

towards the outer surface due to surface dehydration. Steam is formed from diffused

water on outer surface that absorbs latent heat of vaporization from adjacent layer of oil,

creating a layer of steam that protects food from oil absorption and prevents burning or

charring (Blumenthal 1991, Moreira and others 1988, Varela 1988). Leaching occurs as

lipid and other liquefied food mass flows out of food and into surrounding oil as the

interior heats (Blumenthal 1991).

During oil transfer, hot oil enters capillaries of the food formed from diffused

water migrated to food surface, towards interior of the food filling the void spaces. The

rate of oil entry is a function of viscosity, surface tension, and temperature of oil. A study

by Varela (1988) showed that oil penetration begins once 60% of moisture from food

migrates to the food surface although oil interaction with interior voids is limited. The last

phase of frying is cooking of the interior. The food’s interior is primarily cooked by heat

penetration rather than oil absorption within the food matrix (Stevenson and others

1984).

The surface of a fried food is called crust (Paul and Mittal 1997). Fried foods with

optimal color have a golden brown crust resulting from carbonyl-amine browning

(Stevenson and others 1984). Previous studies showed that temperature and length of

frying associated with the chemical composition of a food product influence browning

color rather more significantly than oil (Stevenson and others 1984). Formation of crust

results from the food’s surface dehydration and fat penetration within the tissue (Varela

1988). Crust formation occurs after approximately 3-6 minutes at standard frying

29

temperatures. Previous studies showed the majority of absorbed oil was concentrated in

crust and outer layers of fried food during frying (Guillaumin 1988) and later moved

towards the interior while cooling (Moreira and others 1997).

Chemical Reactions

Figure 2-3, adapted from Fritsch (1981), postulates the physical and chemical

reactions occurring simultaneously during frying. Physical changes in oil during frying

increase viscosity, color, formation of off-odors, and foaming (Choe and Min 2007).

Chemical changes increase formation of FFA, polymeric compounds, carbonyl

compounds, and decrease in unsaturation. Quantification of break down products are

used to determine oil quality. Hydrolysis breakdown products are directly related to

formation of oil breakdown products in further reactions (Warner 1998).

Frying oil is subjected to elevated temperatures and interacts with air and

moisture resulting in a multitude of chemical reactions altering the oil composition during

frying (Perkins 1988). Hydrolysis, oxidation, and polymerization are primary chemical

reactions occurring simultaneously during frying yielding products categorized as

volatile and non-volatile compounds. Some volatile compounds escape into the

atmosphere while others remain in the oil and undergo further chemical reactions

absorbing into foods, providing flavor (White 1991). Non-volatiles remain in the oil or

food further stimulating chemical reactions contributing to further degradation (Choe and

Min 2007). Non-volatiles such as, polymeric triacylglycerols, oxidized triacylglycerol

derivatives, cyclic substances, and breakdown products (Perkins 1996), alter physical

and chemical properties of oil and fried foods, affecting stability and quality of fried

foods during storage (Choe and Min 2007).

30

As food is heated in oil, moisture from food is released as steam evaporating

which tapers off as frying continues (Choe and Min 2007). This is best described as the

violent reaction of water vaporization from food when first introduced to hot oil. Steam

interacts with triglycerides to liberate free fatty acids while forming monoglycerides,

diglycerides, and glycerol through a process known as hydrolysis. Liquid water

hydrolyzes oil more rapidly than steam because the greater contact surface area

between oil and aqueous phases of the food also favor hydrolysis. Another factor

favoring hydrolysis in frying procedures include chemical alkali residues such as sodium

hydroxide for fryer cleaning. However, frequent replacement of frying oil with fresh oil

has been shown to retard hydrolysis (Romero and others 1998).

Thermal oxidation involves the same chemical mechanisms as autooxidation:

initiation, propagation, and termination. Ground state oxygen is in the triplet state and

double bonds in oil are in the singlet state. Because of thermodynamics, atmospheric

oxygen cannot react directly with double bonds because their spin states are different.

Quantum mechanics demands conservation of spin angular momentum, thus triplet

state oxygen cannot invert to singlet state; and to excite double bonds into triplet state

requires excess energy. However, ground state oxygen overcomes the spin barrier in

the presence of a catalyst (Schaich 2005). Heat, light, metals, and oxidative oxygen

species catalyze radical formation in oil. Hydrogens adjacent to carbon-carbon double

bonds will be abstracted first forming a radical. Energy required to break the carbon-

hydrogen bond on carbon-11 of linoleic acid is estimated to be 50 kcal/mole (Min and

Boff 2002). However, the energy required to break the carbon-hydrogen bond on a

saturated carbon adjacent to single bonds is approximately 100 kcal/mol. Given the

31

different strengths of carbon-hydrogen bonds, variance in oxidation rates for stearic,

oleic, linoleic, and linolenic acids is apparent. Alkyl radical formation by abstracting a

hydrogen from an oil molecule is termed autooxidative initiation (McClements and

others 2008). Alkyl radicals may quickly react with triplet state atmospheric oxygen to

produce peroxyl free radicals. Peroxyl radicals also abstract a hydrogen from oil

molecules forming primary lipid oxidation products, primarily hydroperoxides, with other

alkyl radicals in the propagation phase (Shahidi and Wanasundara 1998). Peroxyl

radicals may also react with other present radicals forming dimers and polymers (Choe

and Min 2005). These successive chain reactions and formation of free radicals

accelerate oxidation. Since hydroperoxides are unstable compounds in deep fat frying,

hydroperoxides break down into alkoxy and hydroxyl radicals by homolysis of the

peroxide bond. Alkoxy and hydroxyl radicals will react with other radicals to form non-

radical products, known as the termination phase. Hydroperoxides also tend to

breakdown via β-scission reaction forming volatile secondary lipid oxidation products

such as aldehydes, ketones, and alcohols (Frankel 1962).

Continued use of degraded oil promotes oil break down past secondary oxidation

products resulting in polymerization reactions. Major decomposition products of frying

oils are nonvolatile polar compounds and triglycerides, dimers, and polymers (Perkins

1996). Dimerization and polymerization are radical reactions formed via Diels-Alder

reaction where triglycerides and free radicals link to form cyclic and non-cyclic polymers

(Nawar 1969). Formation of polymers is dependent on oil type, frying temperature, and

number of fryings (Choe and Min 2007). As the number of fryings increase and frying

temperature increases, the amount the polymer formation increases (Cuesta and others

32

1993). Oils rich in linoleic acid favor polymerization more than oleic acid (Bastida and

Sanchez-Muniz 2001). Formation of cyclic compounds is dependent on degree of

unsaturation and frying temperature (Meltzer and others 1981). As linolenic acid

increases, formation of cyclic compounds increases (Rojo and Perkins 1987). However,

amounts of cyclic monomers are insignificantly associated with further compound

formation, unless linolenic acid exceeded 20% or frying temperatures were between

200-300°C (Choe and Min 2007). Polymers formed from frying are rich in oxygen which

contribute to further oxidation of oil. Polymers also increase oil viscosity, reduce heat

transfer, promote foam formation, darken color, and increase oil absorption in fried

foods (Tseng and others 1996). Polymers also produce as brown-like resin along fryer

sides where oil, metal, and oxygen complex. Resin is formed from oil trapping air

without releasing moisture (Lawson 1995).

Oil Quality

Oil degradation is a complex process with multiple factors affecting the frying

performance of an oil over extended amounts of time. According to Warner (1998),

there are two types of parameters associated with fried food quality: oil/food and

process parameters. Oil/food factors include type of oil and food, unsaturated fatty acid

content in oil, initial oil quality, metal and/or other degradation product concentration in

oil, and antioxidant or antifoaming agent presence. Process parameters include oil

temperature, frying time, type and condition of frying equipment, amount of oxygen

absorbed into frying oil, continuous or batch frying, and heat transfer.

As frying time increases peroxide value (PV), volatile compounds, and foaming

increase. However, PV and volatile compounds then decrease. As frying time increases

FFA, color, viscosity, polymeric material, and polar material increase. Total unsaturated

33

fatty acid content of oil decrease as frying time increases (Shahidi and Wanasundara

1998). These trends are summarized in Figure 2-4 (Warner 1998). According to Paul

and Mittal (1997), a frying oil should be discarded if it is not organoleptically acceptable,

if the total polar materials are greater than 25%, if the acid value of oil is greater than

2.5, or if the smoke point is lower than 170°C.

Lipid oxidation can be assessed by a variety of methods including physical,

chemical, and analytical. However, no one analytical method is considered satisfactory

in detecting all oxidative changes in all food systems. Therefore, researchers

recommend multiple assessments to be conducted to determine lipid oxidation (Shahidi

and Zhong 2005). Lipid oxidation assessment methods can be categorized into five

classifications grouped by what they measure: oxygen absorption, reactant change,

formation of free radicals, formation of primary oxidation products, and secondary

oxidation products (Shahidi and Zhong 2005).

One of the most common quality indicators of fats and oils during production and

storage is peroxide value (PV). Peroxide value is a measure of primary oxidation with

multiple ways to assess its value. Iodometric Titration assay is based on the oxidation of

the iodide ion (I-) by hydroperoxides. Saturated solution of potassium iodide is added to

an oil sample to react with hydroperoxides. The liberated iodine (I2) is assessed by

titration against a standardized solution of sodium thiosulfate and starch as an endpoint

indicator (Shahidi and Wanasundara 1998). Man and others (1999) studied refined,

bleached, and deodorized palm olein (RBDPO), soybean oil, and their blends during

intermittent frying of potato chips at 180±5°C. RBDPO showed an increase in PV on day

3 and a decrease on day 4 until termination of the study, and soybean oil and

34

RBDPO/soybean blend showed an increase in PV on day 1 and a decrease on day 2

until termination. A decrease in PV shows breakdown of hydroperoxides to secondary

reaction products. An oil characterized by minimal PV indicates a more stable oil.

Peroxide value is an indicator of initial oxidation and does not account for secondary

oxidation products.

Assessment of free fatty acids is a method to evaluate oil quality (Choe and Min

2005). Free fatty acids (FFA) of a frying oil used to fry flour dough at 160 °C increased

as the number of fryings performed by the oil increased (Chung and others 2004). Free

fatty acids are thought to be formed during thermal hydrolysis in the frying medium

rather than the water-oil interface (Lascaray 1949, Pokorny 1989). Oils with short chain

and unsaturated fatty acids are more susceptible to hydrolysis because they are more

soluble in water than long chain saturated fatty acids (Nawar 1969). Additionally,

moisture from foods is readily available to form short chain fatty acids through

hydrolysis (Nawar 1969). The degree of unsaturation (more double bonds) influences

thermal degradation more than chain length as supported by a study showing rate of

oxidation of an oil increased as the degree of unsaturation increased (Frega 1999,

Stevenson and others 1984, Warner and others 1994). Other studies show that free

fatty acids stimulate thermal oxidation of an oil (Miyashita and Takagi 1986, Mistry and

Min 1987). Fresh oils suitable for deep fat frying have less than 0.05% FFA and 1.0 meq

peroxides/1 kg of oil (Stevenson and others 1984), although do not provide optimal

conditions for fried food flavor (Blumenthal 1991)

The measurement of total polar materials is considered a better indicator of oil

quality as it assesses all the degraded products rather than initial triglycerides from

35

fresh oil (Fritsch 1981). Polymeric compounds are included in the total polar materials

but can be measured separately by molecular weight using size exclusion

chromatography (Shahidi 2005) as they are the largest class of degradation products in

frying oils (Bansal and others 2010).

According to Warner (1998), fatty acid composition of frying oil determines the

volatile compounds formed and development of fried flavor. Hexanal, pentanal, and 2,4-

decadienal are breakdown products of linoleic acid. Octanal and nonanal are

breakdown products of oleic acid (Warner and others 1997). Warner and others (1997)

investigated a correlation between 2,4-decadienal and fried food flavor of potato chips

and French fries prepared in four different oils. Using a 16-member trained analytical

sensory panel, overall flavor quality of freshly prepared french fries was linked to oleic

acid levels. As the percentage of oleic acid increased, the intensity of fried-food flavor

and overall quality decreased in prepared french fries. Fried food flavor intensity and

levels of 2,4-decadienal decreased as linoleic acid levels decreased This same study

showed french fries prepared over 30 h deteriorated oil with fatty acid profile of 63%

oleic acid and 23% linoleic acid had the highest fried food intensity and flavor quality

scores. Fatty acid composition was associated with fried food flavor, overall flavor

quality, and total polar compounds. Oils with fatty acid profiles of 16-42% oleic and 37-

55% linoleic acid produced moderate fried food flavor, good overall flavor quality, and

low to moderate levels of total polar compounds for freshly fried foods (Warner and

others 1997).

Oil Stability Index

Formic acid and acetic acid are formed as secondary oxidation products at high

temperatures during lipid oxidation (Shahidi and Zhong 2005). Other secondary

36

products can be formed simultaneously from hydroperoxides (Kiritsakis and others

2002). Oil Stability Index (OSI) measures volatiles by recording changes in electrical

conductivity as effluent from oxidized oil is bubbled through water (Gordon 2001).

Induction period is defined as the time elapsed to reach the point of accelerated change

in oxidation rate. The point in time where maximum change occurs in the rate of

oxidation is called the OSI value, where electrical conductivity increases as the

formation of volatile compounds increase (primarily as formic acid). An example of OSI

output can be seen in Figure 2-5. Because oil stability decreased with increasing

temperatures, an instrument measuring OSI exposes oil to elevated temperatures and

excess oxygen to simulate oxidative conditions for shelf-life performance. In 1993, the

OSI method replaced the Active Oxygen Method (AOM) established in 1932 (Feibig

2003), which measured induction period from peroxide value calculations for estimated

stability. Not only is the OSI an automated version of the AOM, but it also eliminates

other solvents from the process. Laubli and Bruttel (1986) conducted a study comparing

the induction period derived from the AOM and OSI (Rancimat, Metrohm, Riverview, FL,

USA), and found a strong correlation coefficient (r=0.987) for six different fats and oils,

indicating the OSI as an effective replacement for AOM. Rancimat OSI™ has become

established over time and has been integrated into other accepted national and

international standards, such as AOCS Cd 12b-92 (American Oil Chemists’ Society,

Urbana, IL, USA) and ISO 6886 (International Organization for Standardization, London,

UK).

The Rancimat™ method has become widely accepted as a method of measuring

OSI because of its ease and reproducibility. The Rancimat™ is a computer controlled

37

device used for determination of oxidative stability of fats and oils. The evaluation

algorithm determines the “break point” or “cusp” of oxidation curve providing induction

period (IP) measurement. The instrument is also able to determine “stability time,” which

is the time until a defined change in conductivity is achieved. Examples of OSIs for

different oils evaluated at 120°C are shown in Table 2-3.

In the Metrohm OSI measurement system, ambient air is bubbled at a constant

flow rate through oil samples at a constant temperature, typically 110°C or 120°C, to

accelerate oxidation. Volatile secondary reaction products, mainly formic and acetic

acid, transfer via tube connected to the reaction vessel to a measuring vessel

containing deionized water. As the deionized water in the reaction vessel receives

volatile compounds, the electrical conductivity of the water is continuously registered as

volatile input increasing electrical conductivity in the vessel. The change in conductivity

is plotted and induction period, defined as time elapsed until secondary reactions occur,

is recorded. Other applications for the Rancimat™ are examination of effectiveness of

antioxidants, oxidation stability of fat and oil containing foods, cosmetics, and biodiesel

fuel. Sample types permissible besides pure, clear, vegetable oils include non-liquid,

pure fats, samples containing fats and oils, emulsion fats, and solid samples (Metrohm

2012).

OSI Rancimat™ methodology on initial oil samples is not a good indicator of how

the oils will react during deep frying as other factors are involved (Tsaknis and Lalas

2002). However, this method can be used to compare the extent of oil degradation from

deep fat frying (Matthaus 2006). In a recent study conducted by Farhoosh and Moosavi

(2007), there was a strong correlation (r2 = 0.9949, 0.9856) between OSI via

38

Rancimat™ at 120°C and total polar compounds (TPC) and between OSI and carbonyl

value (CV), respectively, for used frying oils.

Other Factors Affecting Oil Quality

The ratio of total oil in a fryer to the rate of fresh oil added is defined as the

“turnover rate” (Stevenson and others 1984). Higher oil quality is maintained with a daily

turnover rate of 15%-25%, by mass (Stevenson and others 1984). Replenishing frying

oil with fresh oil periodically decreases the formation of degradation products and

increases oil quality, as a whole (Romero and others 1998). Increased duration of frying

and temperature increases free fatty acid content, polar compounds, and polymers

(Blumenthal 1991). Further intermittent heating and cooling processes encourage

degradation product formation versus continuous heating (Clark and Serbia 1991). As

the oil cools from elevated temperatures, the solubility of oxygen in oil increases,

accelerating oxidation and peroxide formation. Moreover, peroxides sustain further

chemical reactions as temperatures are elevated resulting in further degradation (Clark

and Serbia 1991, Gere 1982). Stevenson and others (1984) recommends using a fryer

that is characterized with a small surface to volume ratio to minimize contact of oil with

air. This method of frying allows for fast and even heat transfer within oil to prevent hot

spots and scorched oil (Paul and Mittal 1997). Regular fryer maintenance prevents

polymerized fat deposits that facilitate gum formation, foam formation, oil darkening and

further degradation (Morton and Chidley 1988, Stevenson and others 1984).

Sensory Science

Sensory evaluation can be defined as techniques used to accurately measure

human responses to foods and minimize potential biases of brand identity and other

information influencing consumer perception (Lawless and Heymann 2010). According

39

to Stone and Sidel (2004), sensory evaluation involves scientific methods used to

evoke, measure, analyze and interpret human responses to food products through

organoleptic organs. Sight, smell, taste, touch, and hearing – sensory evaluation is also

considered a quantitative science in which numerical data is collected to establish

specific relationships between product characteristics and human perception. However,

data obtained from human observation maybe highly variable and conclusions drawn

should be reasonable judgements formed from data, statistical analysis, and results

(Lawless and Heymann 2010).

Sensory evaluation considers precision, accuracy, sensitivity, and avoiding false

positive results (Meiselman 1993). The validity of any test is the ability to measure what

it was designed for and what it was intended to measure (Meiselman 1993). Sensory

test results should reflect perceptions and views of consumers that might buy the

product and should generalize to larger populations to fulfill a test’s predictive validity

(Lawless and Heymann 2010). Test results should correlate with instrumental analysis,

process or ingredient variables, storage factors, shelf-life, or other conditions affecting

sensory properties (Lawless and Heymann 2010). Correlations are used to evaluate the

relationship between instrumental measurement and sensory perception to predict

consumer responses or evaluate quality control parameters (Szczesniak 1987). To

minimize error, sensory tests should not overlook important differences (Lawless and

Heymann 2010). Ways to minimize panelist deviations include using guidelines for

preparation and serving of samples under controlled conditions, labeling samples with

random numbers to prevent bias from labels, using varied order of presentation, and

establishing standard procedures for temperature, volume, and time allowance to

40

prevent variation (Meilgaard and others 2006). Other principles of good practice in

sensory analysis deal with providing a sensory testing environment including climate

control, odor-free, excellent ventilation, noise and distraction free, temperature (20-

22°C) and relative humidity (50-55%) control (Meilgaard and others 2006). Additionally,

water and unsalted crackers are most often provided to cleanse panelists’ palette

between samples (Lucak and Delwiche 2009).

Sensory data is collected as human perceptions of food results from complex

sensory and interpretation processes. Sensory perceptions are difficult to predict from

instrumental measures because instruments lack the sensitivity and

mechanical/chemical manipulation of food of the human sensory system (Lawless and

Heymann 2010). Instruments also fail to give data that interpret sensory experience by

the human brain prior to responding. Human sensory experiences are interpreted by the

brain, and give meaning within reference, are evaluated relative to personal

expectations, and involve the integration of multiple simultaneous and/or sequential

inputs. Sensory experiences are chains of perceptions rather than stimulus and

response (Meilgaard and others 2006). Therefore, only human sensory data can model

how consumers will perceive and react to food products in real life.

Testing

In sensory analysis, there are three types of tests: discrimination, descriptive,

and affective (Eggert and Zook 1986). Discrimination or difference tests evaluate if

products are perceptibly different by sensory measures in any way. Difference tests are

analytical measurements that employ 25-40 panelists screened for sensory acuity and

are familiar with test procedures. Difference tests are popular due to simple data

41

analysis. Some examples of difference tests are triangle tests, duo-trio tests, and paired

comparison (Lawless and Heymann 2010).

Descriptive tests evaluate how products differ in specific sensory characteristics.

Descriptive tests are also analytical tests that utilize trained panelists screened for

sensory acuity and motivation. These tests quantify perceived intensities of sensory

characteristics of a product and can be related to consumer acceptance information and

instrumental data (Lawless and Heymann 2010). Some examples of this type of test are

Quantitative Descriptive Analysis® (QDA®) (Stone and Sidel 2004), Flavor Profile®

method (Caul 1957), and Spectrum Method® (Meilgaard and others 2006).

Affective tests evaluate how well products are liked or preferred. Affective or

hedonic tests quantify the degree of liking or disliking of a product through untrained

panelists familiar with the product (Lawless and Heymann 2010).

Scales

Acceptance testing scales the degree of acceptability of foods and provides

some information about whether a product is liked of disliked in some absolute sense

(Lawless and Heymann 2010). The most common hedonic scale is the 9-point hedonic

scale or degree of liking scale seen in Figure 2-6 (Peryam and Girardot 1952). The 9-

point hedonic scale assumes consumer preferences exist on a continuum and that

preference can be categorized by responses based on like and dislike. Descriptive

words selected on scales are based on approximately equal differences from one

another (Peryam and Pilgrim 1957). Acceptance testing scale assigns numerical values

as response choices for statistical analysis, with 1- extremely dislike and 9-extremely

like (Peryam and Girardot 1952). The values can then be analyzed using parametric

statistics, t-tests on means for two products or analysis of variance (ANOVA) with

42

comparison of means between two products (Lawless and Heymann 2010). Acceptance

tests are easy to use and can be applied to foods, beverages, and non-food products.

However, there are criticisms for this scale. Moskowitz (1980) reported 9-point scales

have potential problems associated with unequal spacing of options. Direct scaling

methods indicate the distances from neutral to like slightly or dislike slightly are shorter

than others. Another criticism declares the scale to be less efficient because the neutral

category allows consumers to avoid the extreme categories (Moskowitz 1982).

Another scaling method commonly used in acceptance testing are line scales or

visual analog scales (VAS) in which panelists indicate their response by marking a slash

on a line (Baten 1946). Panelist responses are recorded as the distance of their mark

from one end of the scale (Lawless and Heymann 2010). Typically, only the anchors of

the line are labeled and marked with a short line perpendicular to the recording line. For

acceptance testing, the “lower” end is often labeled “dislike extremely” and the “higher”

end is labeled “like extremely” (Lim and others 2009). The main advantage of line

scales is that they appear more continuous and less limited to the recording panelist,

although many panelists will use sections of the scale unless directed by panel

moderators. An example of an unmarked hedonic line scale is seen in Figure 2-6. Other

variations of line scaling applied to acceptance testing include line scales with pips

(Villanueva and others 2005) and simplified labeled affective magnitude scale (SLAM)

(Wright 2007).

Another scale applied to acceptance testing is the Just-About-Right (JAR) Scale.

JAR scales combine intensity and hedonic judgements and use opposite end anchors

with a center point (Rothman and Parker 2009). The end anchors are labeled “too little”

43

and “too much,” and the center point is labeled “just about right.” “Just about right”

labels are used because a “just right” label may be associated with too strong of a

commitment. For example, the anchor labels for evaluating soup might be “not salty

enough” and “much too salty,” resulting in a preference to saltiness versus affective

scoring (Shepard and others 1989). JAR scales provide direct information on specific

attributes to be optimized and be used to compare different versions of a product

(Lawless and Heymann 2010). Implications to JAR scales exist because panelists differ

in understanding what the attribute in question is referring to, thereby limiting JAR

scales to simple attributes, such as sweetness and saltiness. End points for JAR rating

must be true opposites and complex attributes should be avoided, such as creaminess.

JAR ratings also do not indicate how much to change a product to yield a better result,

and in complex systems, how altering one attribute may affect ratings of another

(Rothman and Parker 2009). JAR scales also assume that each attribute has an

optimum as defined by the panelist. If consumers have mentalities of “more is always

better” or “any of this is bad”, JAR scales are not effective (van Trijp and others 2007).

Evaluation

While other physical parameters and analytical indices provide measurement of

oil decomposition, sensory evaluation of oils is an important assessment method in

industry. Human sensory detection of off-flavors and off-odors by taste and smell is a

method to determine if a food is of adequate quality. According to the American Oil

Chemists’ Society (AOCS), edible oils can be graded using the Flavor Quality Scale

(Table 2-4) to describe lipid oxidation (Warner 1985). Some terms used to characterize

flavor are buttery, nutty, beany, grassy, watermelon, painty, and fishy (Civille and Dus

1992). Some terms used to describe oxidized oil by process are hydrogenated,

44

oxidized, reverted, light-struck, and rancid (Civille and Dus 1992). In this case, QDA® or

other descriptive analysis methods are performed by a trained panel since the

sensitivity to off flavors and off odors can vary among panelists. From the quantitative

and qualitative data of the trained qualitative descriptive panels, a more sensitive

sensory panel can be conducted to determine more precise levels of sensory changes

(Lawless and Heymann 2010).

Fioriti and others (1974) conducted a study where a variety of commercial fats

were oxidized at elevated temperatures (37.8°C, 60°C, and 75°C), where oxidation was

evaluated objectively using instrumental methods and organoleptically trained panels.

At both 37.8°C and 60°C, strong R2 values ranging from 0.80-.095 and 0.90-0.99 were

found when correlating peroxide value and flavor score, respectively. Other

investigators observed partial correlation coefficients of OSI and sensory induction

periods for light exposed soybean oil where resultant data were significantly different

from zero and P ≤ 0.001, indicating OSI as a good measure of oxidation for partially

oxidized oils (Coppin and Pike 2001).

45

Table 2-2. Desirable qualities of refined palm oil

Parameter Physical (RBD) Chemical (NBD)

Free fatty acid (16:0) (%) 0.1 0.1

Peroxide value (mEq/kg) 0 0

Moisture and impurities (wt %) 0.1 0.1

Iron, (mg/kg), max. 0.12 0.12

Copper, (mg/kg), max. 0.05 0.05

Phosphorus, (mg/kg), max. 4 4

Lovibond color, max. (5.25 inch cell) 3.0R -

Soap content (mg/kg) - 0

Basiron 2005

Table 2-3. Oxidative stability index (OSI) values at 120°C

Sample Induction period (h) Reference

Peanut oil 3.25 Laubli and Bruttel 1986

Sunflower oil 2.27 Laubli and Bruttel 1986

Olive oil 6.42 Laubli and Bruttel 1986

Lard 0.33 Laubli and Bruttel 1986

Margarine 6.17 Laubli and Bruttel 1986

Cooking butter 5.03 Laubli and Bruttel 1986

Palm oil 10.89 Anwar and others 2003

Cottonseed 3.06 Anwar and others 2003

Canola 3.87 Anwar and others 2003

Soybean 2.61 Anwar and others 2003

Table 2-1. Fatty acid composition of various vegetable oils C12:0 C14:0 C16:0 C18:0 C18:1 C18:2 C18:3

Palm ND-0.5 0.5-2.0 39.3-47.5 3.5-6.0 36.0-44.0 9.0-12.0 ND-0.5 Palm kernel 45.0-55.0 14.0-18.0 6.5-10.0 1.0-3.0 12.0-19.0 1.0-3.5 ND-0.2 Palm olein 0.1-0.5 0.5-1.5 38.0-43.5 3.5-5.0 39.8-46.0 10.0-13.5 ND-0.6 Canola ND ND-0.2 2.5-7.0 0.8-3.0 51.0-70.0 15.0-30.0 5.0-14.0 Soybean ND-0.1 ND-0.2 8.0-13.5 2.0-5.4 17.0-30.0 48.0-59.0 4.5-11.0

FAO 2001

46

Table 2-4. AOCS Flavor Quality Scale

Flavor grade Description

10 (Excellent) Completely bland

9 (Good) Trace of flavor by not recognizable

8 Nutty, sweet, buttery, corny

7 (Fair) Beany, hydrogenated, popcorn, bacony

6 Oxidized, musty, weedy, burnt, grassy

5 (Poor) Raw, reverted, rubbery, watermelon, bitter

4 Rancid, painty

3 (Very poor) Fishy, buggy

2 Intensive objectionable flavors

1 (Repulsive) Flavor intensity at presented concentration rated slight

Adapted from Warner 1985

47

Figure 2-1. Flow diagram of a palm oil mill

Figure 2-2. Frying oil quality curve

48

Figure 2-3. Deep fat frying diagram

Figure 2-4. Physical and chemical changes of oil during deep-fat frying

49

Figure 2-5. Example of OSI output from Professional Rancimat™ 892

Figure 2-6. Example of an unmarked hedonic line scale

50

CHAPTER 3 MATERIALS AND METHODS

Materials

Soybean and canola oils were obtained from local supermarkets (Publix Super

Markets, Inc. Lakeland, FL) and palm oil and palm kernel oil were obtained from JE

Edwards International, Inc. (Braintree, MA). Pure soybean oil was used as the industrial

frying oil control for sensory comparison. Oil blends were developed combining soybean

oil or canola oil with varying percentages of palm oil (Table 3-1) or palm kernel oil

(Table 3-2). The oils were blended to attempt to optimize pourability at room

temperature and estimated frying stability. All oils and oil blends were transferred or

mixed in plastic containers, headspace flushed with nitrogen, and stored at 4°C until

further use.

Approximately 145 kg of fresh unbreaded chicken wings, separated into first and

second joint wing sections, were obtained from Pilgrim’s Pride Corporation (Live Oak,

FL, USA) and stored at -18°C until further use.

Sample Preparation

Palm oil (P) and palm kernel oil (PK) are solid at room temperature and were

blended with soybean (S) or canola oil (C) using a controlled heat mixer, (Cooking Chef

Model KM080AT, Kenwood USA, Upper Saddle River, NJ). Liquid oils were added to

the controlled heated mixer fitted with a flexible beater attachment and heated to

43.3±2°C for 2 min at minimum mixing speed (48 rpm). Palm oil and/or palm kernel oil

was added to the mixing bowl and blended for 8 min until homogenous. A total of 25

blends were developed for fatty acid profile analysis, pourability at room temperature,

and estimated frying stability using P/S, P/C, PK/S, and PK/C at the following

51

percentages: 25/75, 50/50, 75/25, 80/20, 85/15, 90/10. Fresh oils and oil blends were

transferred to plastic containers (1.42 L, polypropylene) headspace flushed with

nitrogen, capped and stored at 4°C until further use.

Fatty Acid Composition

Fatty acid composition of initial and used oils and blends were determined using

Method 985.1 (AOAC Official Methods of Analysis 1990) after esterification. Fatty acid

methyl esters (FAMEs) were prepared using a modified method described by Maxwell

and Marmer (1983). Fatty acid methyl ester compositions of the soybean oil and palm-

canola oil blend were quantitatively determined by gas chromatography. Approximately

20 mg of oil was placed into a 15 mL centrifuge tube and dissolved in 1.0 mL of

isooctane. 100 µL of 2 N KOH in methanol (1.1 g/10 mL) was added and the tube was

vortexed for 120 seconds and then centrifuged for 5 minutes to separate the layers.

Lower methanol layer was removed, and a small amount of anhydrous sodium sulfate

was added to the tube and the contents were stirred and allowed to rest for 30 minutes.

The mix was then centrifuged, and approximately 1.5 mL of the top layer containing

methyl esters were transferred using a transfer pipette to a GC vial. Vials were stored at

-20°C until further analysis. Three aliquots were sampled for each blend.

A model 6890 series (Agilent, Santa Clara, CA) gas chromatograph was

equipped with split-splitless injector, a 0.25µm film DB-225 column 30 m x 0.25 mm ID

(Agilent Technologies, Santa Clara, CA), and flame ionization detector (FID). Carrier

gas flow (helium) was 0.8 ml/min. Conditions for analysis were: injection port, 230°C,

initial temperature 120°C, final temperature 220°C, and temperature program rate,

4°C/min. The injector split ratio was 1:50. The fatty acid methyl ester reference standard

used was 37 Supelco Component FAME Mix (Supelco, Bellefonte, PA). Fatty acid

52

composition was calculated by the percent area of each peak of total area of fatty acid

peaks.

Oxidative Stability Index

Oil blend fry life was estimated using a modified Rancimat method (Rancimat ™

Model 892, Metrohm USA Inc., Riverview, FL). Metrodata StabNet Computer Software

version 1.0 full (Metrohm USA Inc., Riverview, FL) was used to determine induction

period of oil blends at 175°C to mimic changes at deep fat frying temperatures.

Oxidative Stability Index (OSI) determination method was created with parameters of

sample temperature of 175°C and calibrated with auto temperature correction (less than

±3°C), gas flow rate of 20.0 L/h, and a maximum level for conductivity set to 50 µS/cm.

Approximately 3±0.1 g of experimental oils were weighed in separate reaction vessels

with 60-mL of deionized water added to measurement vessels, in triplicate. Oil blends

with the longest estimated fry life (OSI) and still pourable at room temperature, were

selected for deep fat frying analysis.

Melting Range

Palm and palm kernel oils were melted and blended with canola or soybean oils

to form blends (Table 3-1, 3-2). Five milliliters (5-mL) of each blend were prepared in

15-mL conical tubes and frozen for 12 h at -18°C. A water bath heated to 10°C above

the suspected melting range of the component mixtures was used to determine the

initial melting point. Approximately 1-mL frozen oil blend was packed into a sealed

pipette tube with a digital thermometer and flexible thermocouples inserted inside the

blend. Melting range was visually determined as temperature of initial melting to

temperature of completely liquid sample, in duplicate.

53

Deep-Fat Frying

Two thousand six hundred separated chicken wing sections, 1300 drumettes and

1300 midjoints, were allowed to thaw at 4°C for 48 h before frying. Thawed, unbreaded,

skin-on chicken wings sections were separated into drumettes and midjoints.

The 40 palm/60 canola oil blend (28.4 L) and soybean oil were placed in each fry

well of the Solstice Supreme RL-SSH55-JS (Pitco Frialator, Inc., Concord, NH), and oils

were heated to 175± 5°C. Two frying baskets per oil were filled with a total of 2.2 kg of

25 drumettes and 25 midjoints and then simultaneously deep-fat fried in each oil for 8

minutes to an internal temperature of 165°C measured by a C22 food thermometer

(Comark Instruments, Norfolk, Norwich, UK). Wings were removed and immediately

presented to panelists for sensory evaluation.

Each oil was used for 6 h on Day 1 and Day 2. Day 3 was limited to 5 h due to

insufficient supply of chicken wing sections, for a total of 53 h of intermittent heating and

cooling of oil and resulting in 26 batches of chicken wings for each frying variable. At the

end of each day, oils were cooled to room temperature (22±3°C), covered, and

remained in the fryer overnight. There was no oil replenishment for the duration of

study. Samples were fried over three consecutive days to mimic some restaurant

operations. On Day 1 and 2, nine batches were fried each day per oil comprising of one

batch per hour and every half hour during sensory evaluation. On Day 3, eight batches

were fried in total, one batch per hour and every half hour during sensory evaluation.

Every batch 40-mL of each oil was sampled. See Figure 3-1 for frying and sampling

schedule and Table 3-3 for corresponding time elapsed per batch. All oil samples were

stored in individual 50-mL glass conical centrifuge tubes with screw-cap lid at -18°C

until further analysis. One midjoint and one drumette per oil were stripped and deboned

54

within five minutes after frying and 5.0 g chicken wing were placed into 15-mL amber

vials with screw top polypropylene cap for solid phase mircoextraction (SPME) analysis.

The vials were stored at -18°C until further use.

Color

The International Commission on Illumination (CIE) L*a*b* values of oil samples

were measured using a HunterLab ColorQuest XE Spectrophotometer (HunterLab,

Reston, VA) equipped with EasyMatchQC computer software. The instrument was

operated in Reflectance Specular Included mode and calibrated using the light trap and

white calibrated tile. Absorbance values were measured in visible range (400-700 nm).

Oil samples were placed into 20 mL optically clear glass transmission cells with fixed

path length of 10 mm for each measurement. The procedure was repeated in duplicate.

Free Fatty Acids

Free fatty acids were determined using MQuant Free Fatty Acids Test Strips

(EMD Millipore, Billerica, MA). The assay used is a rapid dipstick method recommended

for monitoring quality of deep-frying oil in restaurants by semi-quantitatively measures

concentration of free fatty acids by visual comparison of reaction zone on test strip with

provided color scale range (0.5 – 3.0 mg KOH/g). Test strips were purchased directly

from EMD Millipore and stored in closed tube held at 25°C. The reaction zone of test

strip was immersed in oil blend for 2 s and then removed. After 30 s, the color field was

determined using reaction color zone legend provided by the manufacturer. Results

were recorded as milligrams KOH necessary to neutralize free fatty acids in 1 g of lipid

sample (mg/g KOH) (O’Keefe and Pike 2010). The procedure was repeated in triplicate

for each oil blend sample.

55

Volatile Compound Analysis

Chicken wing sections (1.3±0.1 g) prepared in 40 palm/ 60 canola oil blend and

soybean oil and 1.3 g sodium chloride were accurately weighed and transferred to 40-

mL amber glass vials capped with polypropylene caps fitted with specialized septa

(Supelco, Bellefonte, PA) for SPME. Sodium chloride (Morton® Salt, Chicago, IL) was

added to inhibit microbial growth during analysis. Volatiles were extracted by SPME

using a 2 cm fiber (Supelco, Bellefonte, PA) comprised of coated

divinylbenzene/Carboxen on polydimethylsiloxane (DVB/CAR/PDMS) 50/30 μm via a

manual SPME fiber assembly holder for 30 minutes while heated in a carbon fiber

heating block at 50°C to obtain headspace equilibrium. SPME extracted volatile

compounds were sheathed by the fiber assembly and immediately transferred to the

injection port of a Shimadzu GC/MS (Shimadzu, Columbia, MD) and held at 275°C in

the injection port for five minutes allowing volatile compound release from fiber to a DB-

5 capillary column (Agilent Technologies, Santa Clara, CA) and cut by Dean’s Switch to

a second DB-5 column under the same temperature program and analyzed by MS in

scanning mode. Compounds detected by MS were compared to National Institute of

Standards & Technology (NIST) and Shimadzu Flavor & Fragrance databases for

matching mass fragmentation patterns to known compounds.

Sensory Evaluation

Sensory panels were conducted at the University of Florida by consumer

panelists. Chicken wings were fried at 175±5°C for 8 min and served within 5 min to

panelists. Chicken wings were randomly assigned three digit numbers using a random

number generator and sample plates used were labeled by corresponding three digit

numbers. Each panelist received two wing sections as a drumette and midjoint per oil

56

on each sample plate. Chicken wing sections were presented to panelists at

approximately 165°C. Orders of presentation were randomized and presented to

panelists an equal number of times. Both fried chicken wings were analyzed by a

consumer acceptance test to determine the acceptance of chicken wings prepared in

palm-canola blend side by side with chicken wings prepared in soybean oil. All

evaluations were conducted in private booths under white light and each panelist

received deionized water and an unsalted cracker to cleanse their palate between

samples.

Chicken wing sections prepared in both oils were evaluated by untrained

consumers for overall appearance, overall liking, overall flavor, off-flavor, overall texture,

crispiness, juiciness, purchase intent, and preference. The hedonic line scale used to

evaluate overall appearance, overall liking, overall flavor, and overall texture ranged

from 0-100 where 0 = dislike extremely to 100 = like extremely. Off-flavor and crispiness

used a similar scale except 0 = none, 0 = extremely soft and 100 = high, 100 =

extremely crisp, respectively. Juiciness and purchase intent were scored on a 5-point

scale. Evaluations were conducted on Day 1, 2, and 3 every half hour for 2 hours.

Appendix A provides the ballot used during sensory evaluations. On Day 1, 2, and 3,

there were 106, 96, and 93 panelists, respectively.

Statistics

Fatty acid composition of oils between Hour 0 (Batch 0) and Hour 53 (Batch 26)

was analyzed for statistical significance using Microsoft Excel 2010 for Windows version

14.0.7166.500 (Microsoft Corporation, Redmond, WA) using “t-Test: Two-sample

Assuming Equal Variances.” Color values of oils were analyzed for statistical significant

using an analysis of variance (ANOVA) (R Foundation for Statistical Computing, Vienna,

57

Austria). Separations of significant color values by hour were analyzed by Tukey’s HSD

test using R version 3.3.0 (R Foundation for Statistical Computing, Vienna, Austria).

Sensory scores were analyzed for statistical significance using a two way ANOVA

factorial design ran in blocks (R Foundation for Statistical Computing, Vienna, Austria).

Separations of significant sensory means by day, oil, or day by oil interaction were

analyzed by Tukey’s HSD test using R version 3.3.0 (R Foundation for Statistical

Computing, Vienna, Austria) for each attribute evaluated. Preference significance was

established by day using a statistical table of critical minimum values required for

significant preference (α = 0.05) from (Lawless and Heymann 2010). All analyses

unless otherwise stated consider only the 93 panelists who returned every day. Refer to

appendix B and C for missing panelist data for each oil.

58

Table 3-1. Palm and other vegetable oil blend combinations (%)

Blend Palm oil Canola oil Soybean oil

25/75 PC 25 75 -

40/60 PC 40 60 -

50/50 PC 50 50 -

75/25 PC 75 25 -

80/20 PC 80 20 -

85/15 PC 85 15 -

90/10 PC 90 10 -

25/75 PS 25 - 75

50/50 PS 50 - 50

75/25 PS 75 - 25

80/20 PS 80 - 20

85/15 PS 85 - 15

90/10 PS 90 - 10

Table 3-2. Palm kernel and other vegetable oil blend combinations (%)

Blend Palm kernel oil Canola oil Soybean oil

25/75 PKC 25 75 -

50/50 PKC 50 50 -

75/25 PKC 75 25 -

80/20 PKC 80 20 -

85/15 PKC 85 15 -

90/10 PKC 90 10 -

25/75 PKS 25 - 75

50/50 PKS 50 - 50

75/25 PKS 75 - 25

80/20 PKS 80 - 20

85/15 PKS 85 - 15

90/10 PKS 90 - 10

59

Table 3-3. Time equivalent per batch

Batch Hour

0 0

1 0*

2 1

3 1.5

4 2

5 2.5

6 3

7 4

8 5

9 6

10 24

11 25

12 25.5

13 26

14 26.5

15 27

16 28

17 29

18 30

19 48

20 49

21 49.5

22 50

23 50.5

24 51

25 52

26 53

0* indicates time elapsed to heat oil to temperature

60

Figure 3-1. Flow chart for frying chicken wing sections and sampling of wings and oils

61

CHAPTER 4 RESULTS AND DISCUSSION

Blend Screening

Base oil OSI values using the modified Rancimat™ method are reported in Table

4-1. 100% palm kernel oil had the longest induction period (0.62±0.03 h, n=4) and

soybean oil had the shortest induction period (0.11±0.01 h, n=4). Modified Rancimat™

method revealed 90/10 PC, 90/10 PS (Table 4-2), and 90/10 PKC (Table 4-3) blends

had the longest induction periods, 0.40, 0.36, 0.35 h, respectively, and therefore longest

predicted fry-life. Because induction period of oil is defined as time elapsed until a

maximum change in electrical conductivity of water is reached, a longer induction period

is associated with higher stability. Longer induction periods are attributed to higher

percentages of saturated fats since oxidation rate has been reported to increase with

increasing unsaturated fatty content (Warner and others 1994). However, these blends

were not pourable at room temperature and too difficult to handle (Bessler and

Orthoefer 1983). Palm oil blends comprising of P ≤ 0.50 had the shortest induction

periods with a range of 0.08-0.11 h, and palm kernel blends with S ≥ 0.50 had the

shortest induction periods. Base oil melting ranges were reported from previous studies

(Table 4-1). Melting ranges of blends were determined for pourability at room

temperature (Table 4-2, 4-3). As palm or palm kernel oil percentage in blend increased,

melting range temperatures increased due to the higher melting ranges of saturated

fatty acid components. After screening all blends, 40/60 PC blend (OSI=0.10 h) was

selected for deep-fat frying by predicted fry-life, melting range, and pourability at room

temperature.

62

Fatty Acid Composition

Changes in fatty acid compositions of frying oils between Hour 0 (Batch 0) and

Hour 53 (Batch 26) is shown in Table 4-4 (40/60 PC) and Table 4-5 (Soybean). After

Hour 53 (Batch 26) for both 40/60 PC and soybean oils, minimal changes were seen in

fatty acid compositions. Table 4-4 (n=3) shows a significant decrease for 40/60 PC in

oleic (18:1), linoleic (18:2), and γ-linolenic acids (18:3n6, GLA) over time. No significant

differences were seen between 40/60 PC Hour 0 and Hour 53 (Batch 26) in other fatty

acids. Table 4-5 (n=3) shows a significant increase for soybean oil in palmitic (16:0),

stearic (18:0), and oleic (18:1) acids and a significant decrease in linoleic (18:2) and

GLA (18:3n6) acids. No significant difference was seen between fresh soybean oil and

Hour 53 (Batch 26) in α-linolenic acid (18:3n3, ALA). Decreases in polyunsaturated fatty

acids for both oils are attributed to destruction of double bonds by oxidation, scission,

and polymerization (Tyagi and Vasishtha 1996). In soybean oil, the decrease in linoleic

(18:2) acid by Hour 53 (Batch 26) is approximately proportional to the increase in oleic

(18:1) acid. According to Warner (1998) total unsaturation decreases with increased

use, suggesting the increase in oleic acid (18:1) for 40/60 PC is possibly due to

hydrogenation of linoleic (18:2) acid during frying. Other changes in fatty acid

composition can be explained by differing fatty acid gradients between fried chicken

wing sections and frying oil matrices resulting in increases or decreases of fatty acid

content from exchange during frying (Sanchez-Muniz and others 1992).

Free Fatty Acid

Free fatty acids (FFA) are reported for each frying oil over time in Table 4-6. Acid

value (AV) can be converted to FFA (expressed at % oleic acid) by the equation: FFA %

oleic = AV x 1.99 (Sanibal and Mancini-Filho 2004). For both 40/60 PC and soybean

63

oils, initial oils (Batch 0) measured 0% FFA which agree with the industry standard of

less than 0.05% FFA for good quality refined oils (Gupta 2005). By Hour 26.5 (Batch

14), FFA reached 0.995% for soybean and between 0 and 0.995% for 40/60 PC. FFA

continued to increase through Hour 53 (Batch 26) for 40/60 PC measuring 0.995%.

Soybean oil remained at 0.995% FFA at Hour 53 (Batch 26). Paul and Mittal (1997)

suggest frying oils should be discarded when acid value exceeds 2.5. For Hour 53

(Batch 26), both oils’ acid values were approximately 0.5. Increases in FFA for both oils

over time were relatively small suggesting minimal hydrolytic degradation occurred by

Hour 53 (Batch 26).

Volatile Compound Analysis

Volatile compounds from chicken wing sections prepared in 40/60 PC and

soybean oils were extracted by SPME and analyzed by MS and compared to database

fragmentation patterns and libraries. All volatiles identified in each sample were

matched to similarity searches greater than 87%. Quantitation of identified compounds

was not established in this study. Chromatograms of volatiles identified in chicken wings

fried in 40/60 PC at Hour 0*, Hour 26.5, and Hour 53 are found in Figure 4-1, 4-2, and

4-3, respectively. Chromatograms of volatiles identified in chicken wings fried in

soybean oil for Hour 0*, Hour 26.5, and Hour 53 are found in Figure 4-4, 4-5, and 4-6,

respectively. Major volatiles common to all chicken wing sections were 3-methylbutanal,

2-methylbutanal, pentanal, 1-pentanol, hexanal, heptanal, 1-octen-3-ol, 2,3-

octanedione, octanal, and nonanal. Hexanal, pentanal (Warner 1998), and 2,3-

octanedione (Young and others 1997) have been selected as breakdown products of

linoleic acid in other studies. Octanal and nonanal are lipid breakdown products of oleic

acid (Warner 1998). 2-methylbutanal, 3-methylbutanal, pentanal, and heptanal were

64

volatile compounds previously identified in fried chicken flavor (Tang and others 1983)

and 1-pentanol, octanal, and 1-octen-3-ol were volatiles identified in aqueous cooked

chicken broth (Wilson and Katz 1972).

2-pentylfuran and 2-heptanone were identified in chicken wings fried in 40/60 PC

Hour 0* and Hour 53 and soybean oils Hour 0*, Hour 26.5, and Hour 53. 2-

methylpropanal was identified at Hour 26.5 and Hour 53 in both oils. Decane was

identified in both oils at Hour 26.5. Acetoin was identified at Hour 0* in both oils. Acetic

acid was only identified in 40/60 PC Hour 0* oil blend. 2-pentylfuran (Smouse and

Chang 1967) was previously identified as a breakdown product of linoleic acid, and 2-

heptanone was reported by Tang and others (1983) as a volatile of fried chicken.

Decane and acetic acid were volatiles previously identified in roasted chicken

headspace using a Tenax® trap (Baruth and others 2013). 2-methylpropanal was

identified in cooked minced chicken breast via purge and trap coupled to GC/MS

(Rivas-Cañedo and others 2009). While acetoin was detected in chicken broth

headspace (Pippen and others 1960), the presence of acetoin did not contribute

significantly to chicken broth flavor. However, the addition of diacetyl at 100ug/100 mL

resulted in detectable differences. Therefore, the conversion of acetoin to diacetyl was

reported by that research group to contribute to the aroma of freshly cooked chicken.

Color

Color was quantified using L*a*b* values for each frying matrix through Hour 53

(Batch 26). L* represents lightness with L*=0 the darkest black and L*=100 the brightest

white. a* and b* values represent color channels where (+a*) is red and (-a*) is green,

and (+b*) is yellow and (-b*) is blue. Color values for both oils are seen in Table 4-7.

Color values for L* and a* were all significantly different for 40/60 PC at Hour 0, Hour

65

26.5, and Hour 53. Color channel b* for 40/60 PC at Hour 0 was significantly different

from Hour 26.5 and Hour 53. Color channel b* for 40/60 PC at Hour 26.5 was not

significantly different from Hour 53. As frying time increased, the L* value for 40/60 PC

significantly decreased, in agreement with literature that oil color darkens with increased

use and polymerization (Choe and Min 2007). Color channel a* of 40/60 PC started

more green and became significantly more red by Hour 53 (Batch 26). Color channel b*

of 40/60 PC remained yellow with increased number of batches and increased frying

time. Color values for L*, a*, and b* were all significantly different for soybean oil at

Hour 0, Hour 26.5, and Hour 53 (Table 4-7). Similar to 40/60 PC, L* values for soybean

oil decreased significantly as frying time increased. Color channel a* of soybean oil also

started more green and became significantly more red by Hour 53 (Batch 26). Color

channel b* of soybean oil also remained yellow with increased number of batches and

increased frying time.

Correlation coefficients (r) between time and L* were strong for individual oils, -

0.9469 and -0.9825 for 40/60 PC and soybean respectively. Correlation coefficients (r)

between time and a* were also strong for individual oils, 0.9978 and 0.9872 for 40/60

PC and soybean, respectively. Color change of frying oils is a visual indicator of oil

deterioration by oxidation. Increases in color intensity are attributed to accumulation of

nonvolatile decomposition products (Abdulkarim and others 2007). This research group

observed oil color darkening in high oleic Moringa oleifera seed oil, canola oil, soybean

oil, and palm olein, throughout 5 days of frying and the rate of frying proportional to

frying time.

66

Sensory

Tables 4-8 through 4-13 show the means of attributes rated by 93 panelists using

a hedonic line scale (0-100) for chicken wing sections prepared in 40/60 PC and

soybean oil. Panelists rated attributes of overall appearance (Table 4-8), overall liking

(Table 4-9), overall flavor (Table 4-10), off-flavor (Table 4-11), overall texture (Table 4-

12), and crispiness (Table 4-13). Off-flavor was rated using a line scale (0-100) where

0=none and 100=high. Crispiness was rated using a line scale (0-100) where

0=extremely soft and 100=extremely crispy. No statistically significant differences

(p>0.05) were found between days, oils, or day by oil interaction for overall appearance,

off-flavor, overall texture, or crispiness. Average ratings for overall appearance, off-

flavor, overall texture and crispiness were 68.7, 30.2, 72.8, and 68.3, respectively.

Overall liking and overall flavor ratings by day increased from Day 1 to Day 3.

Significant differences based on Tukey’s HSD (p<0.05) were found between all chicken

wings fried on Day 1 and 2 and between Day 1 and 3 for overall liking and overall flavor.

A significant difference in overall liking was found between chicken wings prepared in

soybean oil Day 1 and in Day 3 (Table 4-9). For overall flavor (Table 4-10), significant

differences (p<0.05) were found between soybean oil Day 1 and soybean oil Day 2;

soybean oil Day 1 and soybean oil Day 3; and soybean oil Day 1 and 40/60 PC Day 3,

40/60 PC Day 1 and 40/60 PC Day 3, 40/60 PC Day 1 and soybean oil Day 2, 40/60 PC

Day 1 and soybean oil Day 3. The significantly higher ratings in overall liking on Day 3

than Day 1 and in overall flavor on Day 2 and 3 than Day 1 are supported by previous

literature reporting the frying oil quality curve (Blumenthal 1991). New oil heated to

175°C will not produce characteristic color or flavor of thermally conditioned oil for

frying. Ratings suggest Day 1 oil is characterized by “break-in” oil and Day 3 oil is

67

characterized by “fresh” or “optimum” oil resulting in fried foods with higher overall flavor

and overall liking scores.

Juiciness of chicken wing sections fried in each oil was evaluated using a Just-

About-Right (JAR) scale. As seen in Table 4-14, juiciness scores increased from Day 1

to Day 3 in both oils, however, no significant differences (p>0.05) were found in

juiciness between days, oils, or day by oil interaction. Juiciness scores were rated

approximately 2.8, with 3=just-about-right.

Purchase intent of chicken wing sections fried in each oil was evaluated on a 5-

point scale where: 1=definitely would not buy it, 3=might or might not buy it, and

5=definitely would buy it. Table 4-15 shows purchase intent means for chicken wing

sections fried in each oil by day. No significant differences (p>0.05) were found in

panelist purchase intent between days, oils, or day by oil interaction. The average

purchase intent score was approximately 3.6, indicating consumers may or may not buy

chicken wing sections fried in either oil.

Sensory results suggest 40/60PC as an acceptable alternative frying matrix to

soybean oil in overall appearance, off-flavor, overall texture, crispiness, juiciness, and

purchase intent. Correlation coefficients (r) for overall appearance, overall liking, and

overall flavor with day for chicken wing sections fried in 40/60 PC were highly

correlated, r=0.9996, 0.9541, 0.9751, respectively. Correlation coefficients (r) for overall

liking and overall flavor for chicken wing sections fried in soybean oil were also highly

correlated, r= 0.8992 and 0.9012, respectively. While correlations coefficients suggest a

positive linear relationship for these attributes with time, frying oil quality with increasing

time is modeled by a bell-shaped curve (Blumenthal 1991). These results indicate the

68

quality of both oils through the extent of the study did not reach “degrading” or

“runaway” stages.

Table 4-16 shows the results of directional paired comparison test used to

evaluate preference of chicken wing sections prepared in 40/60 PC and soybean oils.

According to the statistical table of critical minimum values required for significant

preference (α = 0.05) from (Lawless and Heymann 2010), when n=106, sixty-four (64)

panelists must prefer one sample to show significant preference. Sixty-seven (67)

panelists preferred chicken wing sections fried in 40/60 PC and thirty-nine (39) panelists

preferred wing sections fried in soybean oil on Day 1 (n=106) showing significant

preference of wing sections fried in 40/60 PC. However, no significant preference of

wing sections fried in either oil on Day 2 (n=96) or 3 (n=93) were found. Preference

results suggest consumers prefer chicken wing sections fried in 40/60 PC more or

similarly to wing sections fried in soybean oil.

Hydrogenation destroys the natural flavor of a fat or oil and imparts a distinct

hydrogenated odor to the fat which is typically removed during deodorization. In a study

by Xu and others (1999), potato chips fried in partially hydrogenated canola oil scored

poorly in flavor and acceptability as the undesirable hydrogenated flavor was evident to

trained oil panelists. From of the results of the current study, 40/60 PC oil blend may

readily replace PHOs in frying applications because of its higher oxidative stability,

acceptable sensory scores, and ease of handling.

69

Table 4-2. Values for palm and other vegetable oil blend combinations

Blend OSI (h) Melting range (°C)

25/75 PC 0.09±0.01 -1.4±0.2 – 28.3±0.1

40/60 PC 0.10±0.00 -0.4±0.2 – 30.5±0.2

50/50 PC 0.11±0.02 3.4±0.3 – 32.5±0.4

75/25 PC 0.19±0.02 19.1±0.1 – 32.9±0.1

80/20 PC 0.20±0.03 18.9±0.2 – 33.5±0.2

85/15 PC 0.21±0.01 19.6±0.3 – 35.4±0.2

90/10 PC 0.40±0.01 20.6±0.4 – 37.1±0.3

25/75 PS 0.08±0.01 2.45±0.2 – 28.6±0.4

50/50 PS 0.09±0.01 16.9±0.1 – 35.1±0.1

75/25 PS 0.31±0.03 18.6±0.1 – 40.5±0.3

80/20 PS 0.29±0.01 18.8±0.1 – 42.3±0.2

85/15 PS 0.30±0.18 19.1±0.1 – 42.3±0.1

90/10 PS 0.36±0.03 19.5±0.1 – 42.6±0.1

OSI values calculated using modified Rancimat™ method at 175°C (n=3)

Melting range (n=2)

Table 4-3. Values for palm kernel and other vegetable oil blend combinations

Blend OSI (h) Melting range (°C)

25/75 PKC 0.17±0.03 4.5±0.1 – 28.1±0.2

50/50 PKC 0.22±0.02 20.0±0.3 – 30.4±0.1

75/25 PKC 0.27±0.02 20.4±0.4 – 32.9±0.4

80/20 PKC 0.31±0.01 21.8±0.1 – 33.2±0.0

85/15 PKC 0.34±0.01 22.5±0.1 – 33.6±0.4

90/10 PKC 0.35±0.01 23.6±0.1 – 33.9±0.1

25/75 PKS 0.12±0.02 12.6±0.1 – 28.9±0.1

50/50 PKS 0.13±0.01 19.8±0.2 – 31.4±0.2

75/25 PKS 0.22±0.01 20.2±0.3 – 33.5±0.3

80/20 PKS 0.24±0.57 20.0±0.0 – 33.7±0.1

85/15 PKS 0.28±0.01 20.5±0.1 – 34.0±0.1

90/10 PKS 0.32±0.02 21.2±0.4 – 34.1±0.1

OSI values calculated using modified Rancimat™ method at 175°C (n=3)

Melting range (n=2)

Table 4-1. Values for pure vegetable oils

Oil OSI (h) Melting Range (°C) Reference

Palm oil 0.40±0.02 33.8-39.2 Sue 2009

Palm kernel oil 0.62±0.03 25.9-28.7 Sue 2009

Soybean oil 0.11±0.01 -27.93‒ -5.68 Fasina and others 2008

Canola oil 0.14±0.01 -28.44‒ -4.38 Fasina and others 2008

OSI calculated using modified Rancimat method at 175°C (n=4)

70

Table 4-4. Fatty acid composition of 40/60 PC over time (%) (n=3)

Hour C16:0 C18:0 C18:1n9 C18:2n6 C18:3n6 C18:3n3

0 19.07±0.14a 3.36±0.02a 51.25±0.20a 18.26±0.13a 4.77±0.01a 0.85±0.03a

53 19.44±0.69a 3.85±0.08a 50.66±0.28b 17.67±0.10b 3.89±0.09b 0.84±0.07a aData in columns with common letters are not significantly different (p>0.05) by T-test.

Table 4-5. Fatty acid composition of soybean oil over time (%) (n=3)

Hour C16:0 C18:0 C18:1n9 C18:2n6 C18:3n6 C18:3n3

0 10.06±0.23a 4.21±0.07a 18.73±0.11a 56.23±0.19a 8.71±0.11a 0.10±0.11a

53 12.17±0.19b 4.64±0.07b 26.26±0.16b 47.32±0.18b 6.38±0.09b 0.22±0.11a aData in columns with common letters are not significantly different (p>0.05) by T-test.

Table 4-7. Color values of frying oils with increasing frying time (n=2)

40/60 PC Soybean

Hour L* a* b* L* a* b*

0 51.72±0.16a -4.74±0.04a 3.90±0.01a 32.20±0.04a -1.02±0.03a 1.90±0.01a

26.5 49.30±0.80b 0.17±0.11b 15.35±0.16b 27.82±0.07b 1.10±0.05b 6.65±0.06b

53 41.97±0.06c 3.50±0.32c 15.54±0.23b 25.98±0.09c 2.10±0.14c 4.06±0.06c aData in columns with common letters are not significantly different (p>0.05)

Table 4-8. Hedonic means for overall appearance (n=93)

40/60 PC Soybean

Day 1 67.10±20.18a 67.59±20.82a

Day 2 69.49±18.76a 67.19±20.69a

Day 3 71.66±18.47a 69.43±a19.24

SE=1.37 aData in both columns and rows with common letters are not significantly different (p>0.05)

Table 4-6. Free fatty acid (FFA) values for oils over time (n=3)

Oil Hour Acid value (mg KOH/g) FFA (% oleic)

40/60 PC 0 0 0

26.5 0 - 0.5 0 - 0.995

53 0.5 0.995

Soybean 0 0 0

26.5 0.5 0.995

53 0.5 0.995

71

Table 4-9. Hedonic means for overall liking (n=93)

40/60 PC Soybean

Day 1 67.97±19.88ab 66.52±20.71a

Day 2 70.71±16.41ab 71.55±18.46ab

Day 3 71.52±18.28ab 71.98±16.82b

SE=1.33 aData in both columns and rows with common letters are not significantly different (p>0.05)

Table 4-10. Hedonic means for overall flavor (n=93)

40/60 PC Soybean

Day 1 63.66±21.39a 62.58±21.52a

Day 2 68.35±17.68ab 70.27±18.12b

Day 3 70.39±18.48b 70.97±17.94b

SE=1.44 aData in both columns and rows with common letters are not significantly different (p>0.05)

Table 4-11. Hedonic means for off-flavor (n=93)

40/60 PC Soybean

Day 1 30.60±30.73a 32.30±28.70a

Day 2 29.75±27.96a 28.67±29.01a

Day 3 30.37±29.93a 29.22±29.93a

SE=3.15 aData in both columns and rows with common letters are not significantly different (p>0.05)

Table 4-12. Hedonic means for overall texture (n=93)

40/60 PC Soybean

Day 1 73.41±20.40a 71.04±19.06a

Day 2 72.57±17.35a 72.75±17.77a

Day 3 74.13±16.16a 72.60±16.67a

SE=1.42 aData in both columns and rows with common letters are not significantly different (p>0.05)

Table 4-13. Hedonic means for crispiness (n=93)

40/60 PC Soybean

Day 1 68.81±16.67a 66.34±18.55a

Day 2 68.54±16.51a 68.05±17.66a

Day 3 70.22±17.73a 67.81±17.73a

SE=0.1.31 aData in both columns and rows with common letters are not significantly different (p>0.05)

72

Table 4-14. Juiciness means using JAR scale (n=93)

40/60 PC Soybean

Day 1 2.72±0.54a 2.80±0.52a

Day 2 2.82±0.44a 2.83±0.50a

Day 3 2.83±0.54a 2.87±0.56a aData in both columns and rows with common letters are not significantly different (p>0.05).

Table 4-15. Purchase intent means using 5-point scale (n=93)

40/60 PC Soybean

Day 1 3.51±1.03a 3.33±1.00a

Day 2 3.69±0.86a 3.63±0.87a

Day 3 3.60±0.86a 3.62±0.92a aData in both columns and rows with common letters are not significantly different (p>0.05).

Table 4-16. Panelist preference of prepared chicken wing sections

Day 1 Day 2 Day 3

40/60 PC 67a 51a 51a

Soybean 39b 45a 42a

Total (n) 106 96 93 aData in both columns and rows with common letters show no significant preference.

73

Figure 4-1. Chromatogram of identified volatiles for chicken wing sections fried in 40/60 PC Hour 0* (Batch 1)

Figure 4-2. Chromatogram of identified volatiles for chicken wing sections fried in 40/60 PC Hour 26.5 (Batch 14)

74

Figure 4-3. Chromatogram of identified volatiles for chicken wing sections fried in 40/60 PC Hour 53 (Batch 26)

Figure 4-4. Chromatogram of identified volatiles for chicken wing sections fried in soybean oil Hour 0* (Batch 1)

75

Figure 4-5. Chromatogram of identified volatiles for chicken wing sections fried in soybean oil Hour 26.5 (Batch 14)

Figure 4-6. Chromatogram of identified volatiles for chicken wing sections fried in soybean oil Hour 53 (Batch 26)

76

CHAPTER 5 CONCLUSIONS

Screening of initial blends revealed blends comprised of 90% palm or palm

kernel oils had the longest induction periods and thus longest predicted fry life.

However, these blends were not pourable at room temperature. Melting range

temperatures also increased as percent palm or palm kernel oil increased. Results

indicated the 40% palm oil/ 60% canola oil blend, characterized by long predicted fry life

and room temperature pourability, to be suitable for frying applications.

Fatty acid composition of both oils changed significantly from fresh oil (Batch 0)

to Hour 53 (Batch 26). Polyunsaturated fatty acid content decreased with increased

frying time indicating lipid oxidation. Low levels of FFA found in both 40/60 PC and

soybean oil Hour 53 (Batch 26) indicate minimal hydrolytic degradation throughout the

study. GC/MS analysis of volatile compounds identified alcohols, aldehydes, ketones,

and a furan previously found in fried chicken and aqueous chicken broth flavor. Some

volatile compounds identified were also attributed to oxidation products of oleic, linoleic,

and linolenic acids. Color results of oils showed darkening and reddening with increased

fry time.

Sensory analysis was performed on chicken wing sections for three consecutive

days to evaluate consumer acceptance of frying matrices through a consumer panel.

Results from the panels revealed no significant differences in overall appearance, off-

flavor, texture, crispiness, juiciness and purchase intent. However, significant

differences were seen in overall liking and overall flavor when comparing means by day,

with higher ratings on Day 2 and 3 than Day 1. Higher ratings indicate oils on Day 2 and

3 were more “thermally conditioned” than Day 1 oils, which result in desirable fried

77

flavor, color, and texture of fried foods. Preference selection significantly favored 40/60

PC on Day 1, but no significant preference on Day 2 or 3, indicating 40/60 PC is

preferred or similarly preferred to wing sections fried in soybean oil.

The study revealed that the frying durations for both 40/60 PC and soybean oil

were not long enough to produce organoleptically unacceptable chicken wing sections

by untrained consumer panelists. Palm-canola oil blend performed similarly to soybean

oil during 53 h of frying (Batch 26) of chicken wing sections. More than 53 h of frying

(Batch 26) would be required to demonstrate significant changes in oil and fried food

quality. Results also indicate 40/60 PC may be used as an alternative frying matrix to

soybean oil without loss of quality in chicken wing sections. Future research may

involve extending the frying duration of the study and evaluating the oxidative stability

and sensory quality of the frying oils and fried foods.

The 40% palm oil/ 60% canola oil blend contains zero trans-fatty acids, is

affordable to produce, and provides acceptable sensory scores, as seen in this study.

This blend is a natural alternative oil that could readily replace PHOs in frying

applications.

78

APPENDIX A BALLOT FOR SENSORY EVALUATION

79

80

81

82

APPENDIX B DESCRIPTIVE SUMMARY STATISTICS FOR MISSING DATA: 40/60 PC

Table B-1. Descriptive summary statistics for missing data: Day 1 (n=13)

Appearance Liking Flavor Off-flavor Texture Crispiness Juiciness

Purchase intent

Min 39.00 19.00 16.50 0.50 44.00 40.50 2.00 2.00

Q1 52.00 54.50 49.50 7.50 69.50 63.50 2.00 3.00

Median 67.00 63.00 67.00 29.00 79.50 67.50 3.00 4.00

Mean 67.96 64.12 60.35 27.31 76.08 68.04 2.69 3.54

Q3 79.50 79.00 75.50 43.50 83.00 73.50 3.00 4.00

Max 93.00 91.00 78.50 63.50 100.00 88.50 3.00 5.00

Range 54.00 80.50 62.00 63.00 56.00 48.00 1.00 3.00

SD 17.53 20.63 18.43 22.78 14.57 11.58 0.48 0.97

Variance 307.23 425.42 339.81 519.11 212.41 134.02 0.23 0.94

Table B-2. Descriptive summary statistics for missing data: Day 2 (n=3)

Appearance Liking Flavor Off-flavor Texture Crispiness Juiciness

Purchase intent

Min 42.50 45.00 45.00 3.00 46.50 60.50 2.00 4.00

Q1 51.25 66.00 62.25 3.75 66.75 63.25 2.50 4.00

Median 60.00 87.00 79.50 4.50 87.00 66.00 3.00 4.00

Mean 63.17 73.00 69.67 18.33 75.00 69.17 2.67 4.00

Q3 73.50 87.00 82.00 26.00 89.25 73.50 3.00 4.00

Max 87.00 87.00 84.50 47.50 91.50 81.00 3.00 4.00

Range 44.50 42.00 39.50 44.50 45.00 20.50 1.00 0.00

SD 22.42 24.25 21.51 25.27 24.78 10.61 0.58 0.00

Variance 502.58 588.00 462.58 638.58 614.25 112.58 0.33 0.00

83

APPENDIX C DESCRIPTIVE SUMMARY STATISTICS FOR MISSING DATA: SOYBEAN

Table C-1. Descriptive summary statistics for missing data: Day 1 (n=13)

Appearance Liking Flavor Off-flavor Texture Crispiness Juiciness

Purchase intent

Min 21.00 10.50 19.50 0.00 25.00 15.00 1.00 1.00

Q1 62.00 37.50 46.50 4.00 52.50 45.50 3.00 2.00

Median 71.00 60.00 51.50 27.00 66.00 68.50 3.00 3.00

Mean 66.31 54.73 49.19 30.65 64.77 63.27 3.00 3.15

Q3 75.00 71.00 60.00 50.50 86.50 81.00 3.00 4.00

Max 84.50 86.00 69.50 86.00 92.50 90.50 4.00 5.00

Range 63.50 75.50 50.00 86.00 67.50 75.50 3.00 4.00

SD 16.45 23.12 14.61 27.56 22.74 15.00 0.71 1.28

Variance 271.06 534.65 213.44 759.31 516.90 90.50 0.50 1.64

Table C-2. Descriptive summary statistics for missing data: Day 2 (n=3)

Appearance Liking Flavor Off-flavor Texture Crispiness Juiciness

Purchase intent

Min 40.50 44.50 40.50 3.00 44.00 46.00 3.00 3.00

Q1 57.25 54.25 52.25 19.50 57.00 47.50 3.00 3.50

Median 74.00 64.00 64.00 36.00 70.00 49.00 3.00 4.00

Mean 63.50 61.83 60.00 27.17 65.00 53.67 3.00 3.67

Q3 75.00 70.50 69.75 39.25 75.50 57.50 3.00 4.00

Max 76.00 77.00 75.50 42.50 81.00 66.00 3.00 4.00

Range 35.50 32.50 35.00 39.50 37.00 20.00 0.00 1.00

SD 19.94 16.36 17.84 21.18 19.00 10.79 0.00 0.58

Variance 397.75 267.58 318.25 448.58 361.00 116.33 0.00 0.33

84

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BIOGRAPHICAL SKETCH

Caitlyn Soriano was born in Bartow, Florida and was raised by her parents,

Edwin and Madolin Soriano, in Winter Haven. She received her Bachelor of Science in

food science and human nutrition from the University of Florida in 2013 with an

emphasis in nutritional sciences. After being selected to participate in “An International

Alliance for Functional Food Research, Education, and Extension” through the UF

FSHN Department, she discovered her underlying passion for food science. Caitlyn

then pursued her graduate education also at the University of Florida, completing her

Master of Science in food science and human nutrition in 2016.